{"meta":{"query_hash":"88f1e3330a18","filters":{"venue":"INFORMS Journal on Applied Analytics"},"cohort_total":83,"direct_labels_cover":0,"predictions_cover":83,"exported":83,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/88f1e3330a18","api":"https://metacan.xera.ac/api/v1/cohort?venue=INFORMS+Journal+on+Applied+Analytics"},"results":[{"id":"W1972551986","doi":"10.1287/inte.2013.0716","title":"Scotsburn Dairy Group Uses a Hierarchical Production Scheduling and Inventory Management System to Control Its Ice Cream Production","year":2014,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Department of Agriculture; Dalhousie University","funders":"","keywords":"Operations research; Production planning; Aggregate planning; Scheduling (production processes); Schedule; Production (economics); Synchronizing; Term (time); Integer programming; Operations management; Computer science; Engineering; Economics; Microeconomics; Algorithm","score_opus":0.010499036831239969,"score_gpt":0.21711851220491413,"score_spread":0.20661947537367414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972551986","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34885004,0.0008079714,0.56750745,0.0010543467,0.00020810905,0.0012513986,0.0023762789,0.011132096,0.06681236],"genre_scores_gemma":[0.74654084,0.0003514924,0.22907433,0.00016482211,0.000038029662,0.00028490415,0.0022733079,0.0003051193,0.02096704],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993217,0.000107277614,0.000032434375,0.00017226084,0.0002556246,0.00011076449],"domain_scores_gemma":[0.9991819,0.00021964993,0.00008621127,0.00015863215,0.0002227815,0.0001307774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012435628,0.00065776304,0.0004115802,0.0008794948,0.0011782207,0.0012254115,0.0010282765,0.00040158269,0.0045582056],"category_scores_gemma":[0.0008525143,0.00044166303,0.0004559898,0.001287882,0.00044261257,0.0005353175,0.0008261541,0.00060325617,0.001274645],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010567422,0.00081385043,0.019184595,0.0002557187,0.00011142922,0.00048994174,0.0004708254,0.566397,0.054840285,0.009401779,0.021308335,0.32566947],"study_design_scores_gemma":[0.00019304463,0.00041250302,0.007236116,0.00003390167,0.000060281876,0.00008029344,0.00023463448,0.9164424,0.015899437,0.0027673303,0.056564346,0.000075819524],"about_ca_topic_score_codex":0.1109334,"about_ca_topic_score_gemma":0.11730982,"teacher_disagreement_score":0.1109334,"about_ca_system_score_codex":0.0032365401,"about_ca_system_score_gemma":0.0054931655,"threshold_uncertainty_score":0.22057539},"labels":[],"label_agreement":null},{"id":"W1976415148","doi":"10.1287/inte.2013.0728","title":"Introduction: 2013 Franz Edelman Award for Achievement in Operations Research and the Management Sciences","year":2014,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Corporate Governance and Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Universiteit van Tilburg; Deltares","keywords":"Management; Operations research; Engineering; Engineering management; Computer science; Economics","score_opus":0.03953833893511348,"score_gpt":0.2854690114059198,"score_spread":0.2459306724708063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976415148","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00096624374,0.019805133,0.0020772056,0.12367553,0.70210046,0.0003023331,0.0019475772,0.0006798422,0.14844556],"genre_scores_gemma":[0.007865015,0.022954704,0.0016476538,0.01761556,0.24422334,0.00024666006,0.0023622785,0.00082786405,0.7022569],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9936334,0.00028772053,0.00027072677,0.00052306766,0.004326583,0.00095839734],"domain_scores_gemma":[0.98123264,0.0008141082,0.00059659756,0.000459808,0.010803109,0.0060938196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0070443633,0.0017328407,0.0018313698,0.0041119363,0.002759304,0.011610931,0.0023047656,0.005121131,0.17849334],"category_scores_gemma":[0.012998486,0.00066592125,0.0014202597,0.0020744277,0.0011142822,0.0042277453,0.004853761,0.0059754993,0.11987232],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015367694,0.000012935085,0.00004991618,0.000046548656,0.0000021856013,0.000012832183,0.000009174701,0.00002493198,0.000046522116,0.0011301042,0.9813182,0.017331298],"study_design_scores_gemma":[0.000009840667,0.000028180582,0.000684639,0.00015401543,0.0000040109694,0.000043089836,0.00003261441,0.00006124003,0.000066794375,0.0012120156,0.997689,0.000014617454],"about_ca_topic_score_codex":0.003426372,"about_ca_topic_score_gemma":0.008113507,"teacher_disagreement_score":0.17849334,"about_ca_system_score_codex":0.004077296,"about_ca_system_score_gemma":0.0067561064,"threshold_uncertainty_score":0.5971197},"labels":[],"label_agreement":null},{"id":"W1979906780","doi":"10.1287/inte.1110.0544","title":"Designing New Electoral Districts for the City of Edmonton","year":2011,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"HEC Montréal; University of Alberta","funders":"","keywords":"Redistricting; Contiguity; Plan (archaeology); Heuristic; Operations research; Population; Computer science; Process (computing); Transport engineering; Tabu search; Engineering; Geography; Legislature; Sociology; Artificial intelligence","score_opus":0.062465748116388636,"score_gpt":0.27094747060065544,"score_spread":0.2084817224842668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979906780","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74032736,0.00072626874,0.15832724,0.0017121327,0.0002893662,0.0035404675,0.0015087114,0.0020391722,0.09152929],"genre_scores_gemma":[0.7569837,0.00027633316,0.20992854,0.00012235243,0.00002998178,0.0012084012,0.0015915575,0.00016847673,0.029690687],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984983,0.00058080995,0.000058838174,0.00020674667,0.00020768178,0.00044757564],"domain_scores_gemma":[0.9987595,0.00022335132,0.000107042346,0.00015049739,0.000345069,0.00041457475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019121106,0.00030453317,0.00059931906,0.0016196157,0.0045160996,0.0044052918,0.0014007251,0.0007303098,0.011106348],"category_scores_gemma":[0.0035460198,0.00063567696,0.0004945625,0.0019311238,0.00095751975,0.000979822,0.0020951428,0.0007197864,0.0015379786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009940853,0.0009183455,0.060592584,0.00065115414,0.000109994086,0.0014023297,0.0071095387,0.29033202,0.007536403,0.123572424,0.049076136,0.45770493],"study_design_scores_gemma":[0.0008734969,0.0013719706,0.07639279,0.00023426098,0.00019603268,0.0006862179,0.034289032,0.41412443,0.0097710155,0.021561416,0.44016176,0.0003376266],"about_ca_topic_score_codex":0.075256556,"about_ca_topic_score_gemma":0.31519347,"teacher_disagreement_score":0.9247434,"about_ca_system_score_codex":0.0046094847,"about_ca_system_score_gemma":0.0106889615,"threshold_uncertainty_score":0.14963704},"labels":[],"label_agreement":null},{"id":"W1982221171","doi":"10.1287/inte.1110.0561","title":"A Decision Support System for Scheduling the Canadian Football League","year":2012,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Saskatchewan; Federated Co-operatives (Canada)","funders":"","keywords":"League; Football; Schedule; Operations research; Scheduling (production processes); Computer science; Decision support system; Business; Engineering; Operations management; Advertising; Political science; Artificial intelligence","score_opus":0.11606419874026568,"score_gpt":0.36549903321524857,"score_spread":0.24943483447498288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982221171","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.110956706,0.00025979063,0.8278795,0.00087233883,0.0001500413,0.0015080773,0.0055708047,0.041474976,0.011327792],"genre_scores_gemma":[0.4103984,0.00015339065,0.58043796,0.00016907183,0.000038841677,0.0007520373,0.003843275,0.00050640304,0.0037006105],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989698,0.0002522684,0.000121249854,0.00024921144,0.00031224784,0.000095314885],"domain_scores_gemma":[0.99644923,0.0019879094,0.00022681594,0.00023260764,0.00083827,0.00026524323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023248496,0.00093328353,0.0005334663,0.0011601986,0.0013753454,0.0018477251,0.0014148093,0.0006880937,0.0076679573],"category_scores_gemma":[0.007308733,0.0005049769,0.00047538098,0.0010334216,0.0003331352,0.0009863935,0.00075127016,0.0007391453,0.0010124159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013375868,0.0007419984,0.0065916674,0.00067674986,0.00012789472,0.0005095368,0.0008525652,0.46094784,0.021153104,0.017318886,0.03729421,0.45244795],"study_design_scores_gemma":[0.00017160458,0.00008136387,0.00066120067,0.000029836447,0.000030679545,0.000035367986,0.00009552344,0.97978425,0.004890574,0.002746548,0.011439759,0.000033209057],"about_ca_topic_score_codex":0.076362535,"about_ca_topic_score_gemma":0.06892751,"teacher_disagreement_score":0.076362535,"about_ca_system_score_codex":0.00303275,"about_ca_system_score_gemma":0.007003123,"threshold_uncertainty_score":0.15183616},"labels":[],"label_agreement":null},{"id":"W1988340906","doi":"10.1287/inte.1070.0316","title":"<b>Call for Papers</b>—<i>Interfaces</i> Special Issue: Applications of Management Science and Operations Research Models and Methods to Problems in Health Care","year":2007,"lang":"en","type":"paratext","venue":"INFORMS Journal on Applied Analytics","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Health care; Government (linguistics); Computer science; Operations research; Management science; Engineering; Political science","score_opus":0.11969148278153804,"score_gpt":0.526337057688987,"score_spread":0.4066455749074489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988340906","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000373274,0.007140527,0.008067942,0.13869463,0.5682771,0.0009566912,0.0051502357,0.0049423594,0.26639715],"genre_scores_gemma":[0.0025161838,0.00869688,0.006525062,0.05709996,0.36034206,0.0009180713,0.005671038,0.006674482,0.5515562],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99228513,0.0014416947,0.00080249354,0.0010309396,0.003801487,0.0006382247],"domain_scores_gemma":[0.93700284,0.020927476,0.00375139,0.0055680526,0.023279686,0.00947042],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.010045662,0.0024129613,0.0031014152,0.004602015,0.002190663,0.019081613,0.0038563926,0.012514088,0.6273741],"category_scores_gemma":[0.05071627,0.0014177719,0.003280082,0.004816504,0.0014434081,0.009786796,0.003921443,0.007344839,0.551278],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009160934,0.000008719127,0.000019566729,0.00005282392,0.0000027077422,0.000008037631,0.0000033084543,0.000015074168,0.00004905101,0.00036020845,0.9926426,0.006828789],"study_design_scores_gemma":[0.00001725973,0.000018128902,0.00018602026,0.00012590819,0.0000044355916,0.000034471446,0.000021591293,0.00014166461,0.00008078483,0.0016135541,0.9977424,0.000013675516],"about_ca_topic_score_codex":0.0012677382,"about_ca_topic_score_gemma":0.0020527255,"teacher_disagreement_score":0.6273741,"about_ca_system_score_codex":0.0042722467,"about_ca_system_score_gemma":0.0042488193,"threshold_uncertainty_score":0.5315056},"labels":[],"label_agreement":null},{"id":"W1990846384","doi":"10.1287/inte.32.2.63.57","title":"Mount Sinai Hospital Uses Integer Programming to Allocate Operating Room Time","year":2002,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":212,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Mount; Integer programming; Schedule; Operations research; Heuristic; Integer (computer science); Operations management; Branch and price; Computer science; Linear programming; Mathematical optimization; Engineering; Operating system; Mathematics; Artificial intelligence; Algorithm","score_opus":0.05208496301005444,"score_gpt":0.3588725518668935,"score_spread":0.30678758885683904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1990846384","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09431165,0.001033653,0.7416353,0.005723389,0.0005206878,0.0009719462,0.003919617,0.0021371695,0.14974652],"genre_scores_gemma":[0.48123696,0.0010508278,0.46166858,0.0005757435,0.00012506857,0.0005065108,0.002128457,0.0003549371,0.05235289],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993857,0.00017213804,0.000025890795,0.00009213604,0.00016907572,0.00015512833],"domain_scores_gemma":[0.9992242,0.0003709294,0.00007672722,0.000044247743,0.0001738579,0.00011003325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012189593,0.0011576656,0.0004854144,0.00094550644,0.00099662,0.0017346885,0.000775609,0.0007380381,0.013044854],"category_scores_gemma":[0.0016981792,0.0006377706,0.0007192557,0.0022945984,0.00045080433,0.0006895439,0.000718577,0.0011575988,0.001672345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021785872,0.0001738567,0.0021859142,0.00015651692,0.00005683672,0.00013061748,0.00012197562,0.8468205,0.001542337,0.02654615,0.022399765,0.09964774],"study_design_scores_gemma":[0.000065927146,0.00012648871,0.0006120836,0.000032163065,0.000016835897,0.000027528216,0.0001237009,0.97374105,0.00096505624,0.005898854,0.01837002,0.000020279633],"about_ca_topic_score_codex":0.102360584,"about_ca_topic_score_gemma":0.18094745,"teacher_disagreement_score":0.102360584,"about_ca_system_score_codex":0.004777466,"about_ca_system_score_gemma":0.0074229743,"threshold_uncertainty_score":0.20352954},"labels":[],"label_agreement":null},{"id":"W1991773164","doi":"10.1287/inte.1110.0612","title":"Quantifying the Contribution of NHL Player Types to Team Performance","year":2012,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Salary; League; Cluster analysis; Value (mathematics); Computer science; Artificial intelligence; Machine learning; Economics","score_opus":0.04719951990944064,"score_gpt":0.2540716229958695,"score_spread":0.20687210308642884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991773164","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.986648,0.00012048482,0.008595792,0.000096616466,0.000016163794,0.00003255345,0.00081442203,0.00004140015,0.0036345343],"genre_scores_gemma":[0.99574524,0.000036629284,0.0023269837,0.00001528321,0.000013597318,0.000016098873,0.00096627144,0.000011733387,0.0008680791],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977575,0.0007173466,0.00013631536,0.0004430444,0.000597317,0.0003485662],"domain_scores_gemma":[0.98676205,0.0056100087,0.0038760868,0.0011588754,0.0015688633,0.001024151],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031466386,0.00056869024,0.00050651014,0.002441975,0.0005222094,0.0014432452,0.00061552995,0.0005882995,0.002283884],"category_scores_gemma":[0.015711008,0.00021097416,0.00039231285,0.0022851601,0.00052248326,0.00083254545,0.0011189273,0.00063679816,0.0009794781],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021176245,0.00009162194,0.9579555,0.000041537598,0.00021615833,0.000059173857,0.00039129908,0.015934335,0.0008541102,0.0008239545,0.00069444696,0.022726154],"study_design_scores_gemma":[0.000010671949,0.00017494502,0.9564,0.000025289874,0.00007485821,0.00008712588,0.0014749799,0.03722502,0.0010624415,0.0020090942,0.0014185103,0.00003703976],"about_ca_topic_score_codex":0.0087751765,"about_ca_topic_score_gemma":0.013055521,"teacher_disagreement_score":0.0087751765,"about_ca_system_score_codex":0.00076950085,"about_ca_system_score_gemma":0.0005069458,"threshold_uncertainty_score":0.017448187},"labels":[],"label_agreement":null},{"id":"W1995161114","doi":"10.1287/inte.2014.0776","title":"Introduction: 2014 Franz Edelman Award for Achievement in Operations Research and the Management Sciences","year":2015,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Centers for Disease Control and Prevention","keywords":"Competition (biology); Management; Analytics; Cover (algebra); Engineering; Operations research; Computer science; Data science; Economics","score_opus":0.14554763526424086,"score_gpt":0.3621413515305761,"score_spread":0.21659371626633522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995161114","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010256834,0.020033725,0.0019012295,0.12597333,0.6873959,0.00027271945,0.0019060314,0.0006626997,0.1608287],"genre_scores_gemma":[0.007462638,0.01851737,0.0013697497,0.01599002,0.21165971,0.00021070233,0.0021169875,0.0006767702,0.74199605],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99416757,0.00026969894,0.0002368871,0.00051143754,0.0039042658,0.0009102279],"domain_scores_gemma":[0.9837377,0.0007088934,0.00051927374,0.00043260187,0.008968922,0.0056325393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0062836283,0.0016430434,0.0017013937,0.0039558094,0.0026805676,0.011460767,0.0022632,0.0048610074,0.18070698],"category_scores_gemma":[0.012750421,0.00063187786,0.001260643,0.0018720718,0.0010687073,0.0042419317,0.0049528927,0.0056426497,0.12192903],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015320726,0.000012582057,0.00005043956,0.000040998508,0.000002173111,0.000011838736,0.000008862517,0.000024277055,0.00004473921,0.0012842832,0.9811809,0.01732357],"study_design_scores_gemma":[0.000009633485,0.000027580967,0.0006584442,0.00013624608,0.000003782073,0.00003750678,0.000031341766,0.00006075905,0.00006320955,0.001197954,0.9977603,0.000013190891],"about_ca_topic_score_codex":0.00298626,"about_ca_topic_score_gemma":0.007110291,"teacher_disagreement_score":0.18070698,"about_ca_system_score_codex":0.0038697019,"about_ca_system_score_gemma":0.006076949,"threshold_uncertainty_score":0.6045251},"labels":[],"label_agreement":null},{"id":"W1998617839","doi":"10.1287/inte.1080.0344","title":"A Spreadsheet Implementation of an Ammunition Requirements Planning Model for the Canadian Army","year":2008,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Spreadsheets and End-User Computing","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Ammunition; Variety (cybernetics); Engineering; Operations research; Engineering management; Operations management; Aeronautics; Computer science; Artificial intelligence; Geography","score_opus":0.09789625560620263,"score_gpt":0.3324277299142118,"score_spread":0.2345314743080092,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998617839","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.090134196,0.0002331904,0.7623191,0.0023307335,0.00018894873,0.0018050577,0.010602308,0.061368,0.071018495],"genre_scores_gemma":[0.1926005,0.00036465732,0.76656,0.00037596075,0.000028125469,0.000613428,0.010244228,0.0031211309,0.026091918],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982998,0.00021808528,0.00015339037,0.00024178685,0.00091129995,0.00017556529],"domain_scores_gemma":[0.99384344,0.0020472594,0.00024882707,0.000700399,0.002802844,0.00035722935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021833023,0.001049504,0.0003066685,0.001693463,0.0016715084,0.002737374,0.0026244072,0.00076349924,0.018828252],"category_scores_gemma":[0.010772579,0.000864294,0.0005739554,0.0018657012,0.00048184465,0.0019662664,0.0008074474,0.0013088599,0.0031753033],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010511258,0.0006670837,0.00810695,0.0005103249,0.00011625192,0.0014152917,0.0038112137,0.23771663,0.032479674,0.056921482,0.14462824,0.51257575],"study_design_scores_gemma":[0.0003955049,0.00027820477,0.005195263,0.0003740596,0.00010631568,0.00032823565,0.0009532917,0.6686831,0.025218535,0.0089120455,0.28927234,0.00028321476],"about_ca_topic_score_codex":0.33843416,"about_ca_topic_score_gemma":0.38668695,"teacher_disagreement_score":0.66156584,"about_ca_system_score_codex":0.0073189423,"about_ca_system_score_gemma":0.014034057,"threshold_uncertainty_score":0.6729285},"labels":[],"label_agreement":null},{"id":"W2002507421","doi":"10.1287/inte.1110.0611","title":"A Strategic Empty Container Logistics Optimization in a Major Shipping Company","year":2012,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Booth University College","funders":"","keywords":"Operations research; Container (type theory); Stock (firearms); Safety stock; Business; Profit (economics); Service (business); Computer science; Operations management; Transport engineering; Marketing; Supply chain; Engineering; Economics","score_opus":0.04407673720646854,"score_gpt":0.28347552139311916,"score_spread":0.23939878418665061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002507421","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.595367,0.00040771204,0.36908048,0.0015452484,0.00014164615,0.0003429269,0.00064743456,0.0016605105,0.03080703],"genre_scores_gemma":[0.9051588,0.00012917788,0.08434646,0.00012274238,0.000021791117,0.00012553179,0.00038776672,0.00005756952,0.009650165],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960345,0.00014644841,0.000013083037,0.00011453733,0.000044419987,0.000078054356],"domain_scores_gemma":[0.99976104,0.000073512456,0.000024080315,0.000017636969,0.00005634934,0.00006741979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069180556,0.00081801275,0.0005881035,0.00045448227,0.0010158495,0.0014048831,0.0005201656,0.000768851,0.004960018],"category_scores_gemma":[0.0006523811,0.00039235118,0.00063285785,0.00055830006,0.0004935323,0.00084122596,0.0008646544,0.00057659304,0.00033907496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036040603,0.00018426833,0.002288941,0.00004658553,0.000038981023,0.00023862834,0.000072243274,0.9662317,0.0020761741,0.0053911246,0.0022737938,0.020797191],"study_design_scores_gemma":[0.00003614454,0.00011691438,0.00040086007,0.0000036793354,0.000014257587,0.00001619612,0.00005941381,0.99645954,0.00067188917,0.0009223243,0.0012905896,0.000008162496],"about_ca_topic_score_codex":0.027790578,"about_ca_topic_score_gemma":0.019715367,"teacher_disagreement_score":0.027790578,"about_ca_system_score_codex":0.0015692097,"about_ca_system_score_gemma":0.0028849533,"threshold_uncertainty_score":0.05525762},"labels":[],"label_agreement":null},{"id":"W2004985180","doi":"10.1287/inte.30.2.41.11673","title":"Air Transat Uses ALTITUDE to Manage Its Aircraft Routing, Crew Pairing, and Work Assignment","year":2000,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Charter; Scheduling (production processes); Operations research; Crew scheduling; Crew; Flexibility (engineering); Navy; Work (physics); Computer science; Operations management; Engineering; Aeronautics","score_opus":0.01623516938582708,"score_gpt":0.24733184391631788,"score_spread":0.2310966745304908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004985180","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20281476,0.0005303419,0.68157554,0.0003571494,0.0001389817,0.0006255896,0.0038529437,0.026909845,0.08319486],"genre_scores_gemma":[0.6259959,0.00043127663,0.3279491,0.00010950375,0.00007788994,0.00022569636,0.0053020217,0.00091445615,0.038994156],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996842,0.000045318116,0.000014764645,0.00007575386,0.00012596184,0.0000539643],"domain_scores_gemma":[0.99960977,0.0000718894,0.00006950027,0.00007034406,0.00012575442,0.000052782783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040979162,0.00068782066,0.00037689737,0.0006204699,0.0006492457,0.0009190141,0.0005782138,0.0002490337,0.0060899546],"category_scores_gemma":[0.0006661783,0.00028027565,0.0003571366,0.00067998905,0.00023017947,0.00065808534,0.0007319368,0.00033250664,0.002146361],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059274846,0.0003125302,0.022191606,0.0001735855,0.000112371046,0.00016935641,0.00049285364,0.29289925,0.019621905,0.010392756,0.043169394,0.6098716],"study_design_scores_gemma":[0.00012389803,0.00035618801,0.013724031,0.000019812253,0.00006217152,0.0001995716,0.0002530245,0.85673505,0.01664905,0.004226597,0.10757702,0.000073661446],"about_ca_topic_score_codex":0.04563597,"about_ca_topic_score_gemma":0.06377198,"teacher_disagreement_score":0.04563597,"about_ca_system_score_codex":0.0008692469,"about_ca_system_score_gemma":0.0016149277,"threshold_uncertainty_score":0.09074068},"labels":[],"label_agreement":null},{"id":"W2014291971","doi":"10.1287/inte.1090.0448","title":"Optimization Helps Shermag Gain Competitive Edge","year":2009,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Supply chain; Supply chain optimization; Procurement; Competitive advantage; Supply chain network; Software; Component (thermodynamics); Computer science; Market share; Total cost; Operations research; Supply chain management; Engineering; Business; Marketing","score_opus":0.01019653572668703,"score_gpt":0.22307428505346844,"score_spread":0.2128777493267814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014291971","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4226217,0.0014873353,0.37017626,0.012279291,0.00028238594,0.0003915664,0.0010384095,0.002511303,0.1892118],"genre_scores_gemma":[0.7709714,0.0006951756,0.20875709,0.00077643327,0.00006803285,0.00009346518,0.000785374,0.00030455942,0.017548474],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992889,0.00022982138,0.00002429388,0.000091180504,0.00022320432,0.00014247089],"domain_scores_gemma":[0.99877065,0.00068692886,0.000101974256,0.000105491585,0.00020427097,0.00013072594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011567915,0.0007230028,0.0005539804,0.0009882043,0.00060243654,0.0025374696,0.00064987625,0.00080677564,0.013336581],"category_scores_gemma":[0.003536214,0.0002671161,0.0004302447,0.0012292824,0.0004059991,0.0018209907,0.00096202875,0.00094063376,0.0018342172],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010671769,0.00092825876,0.0117903715,0.00031770673,0.00008876604,0.00035819283,0.00036755085,0.2607131,0.008903872,0.07445376,0.054160617,0.5868506],"study_design_scores_gemma":[0.00018642882,0.00032853227,0.0038776293,0.00007502088,0.00006314651,0.00013268195,0.0008206648,0.8596702,0.0067425594,0.051471733,0.07658812,0.00004336264],"about_ca_topic_score_codex":0.0046368386,"about_ca_topic_score_gemma":0.012866962,"teacher_disagreement_score":0.013336581,"about_ca_system_score_codex":0.0013567053,"about_ca_system_score_gemma":0.0022630857,"threshold_uncertainty_score":0.04461527},"labels":[],"label_agreement":null},{"id":"W2015655819","doi":"10.1287/inte.1120.0632","title":"Introduction to the Special Issue on Analytics in Sports, Part II: Sports Scheduling Applications","year":2012,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"League; Football; Scheduling (production processes); Analytics; Sport management; Recreation; Operations research; Computer science; Engineering; Advertising; Data science; Business; Political science; Public relations; Operations management","score_opus":0.05280231666078187,"score_gpt":0.34032686957096836,"score_spread":0.28752455291018647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015655819","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023241467,0.08931754,0.107295625,0.052896366,0.66671205,0.00094955857,0.0036001725,0.003437458,0.073467106],"genre_scores_gemma":[0.0070551746,0.0925229,0.030090109,0.025185144,0.65015876,0.00063785986,0.0060760276,0.002181702,0.18609229],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975425,0.00033717405,0.00033801564,0.00050485274,0.001113263,0.00016423244],"domain_scores_gemma":[0.98852414,0.0048762998,0.0005982341,0.0007439892,0.0040490883,0.0012081101],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022438937,0.0020820135,0.002170642,0.004537613,0.0011714692,0.006183738,0.0015086958,0.0027258717,0.058975585],"category_scores_gemma":[0.008777354,0.0009843938,0.0019872834,0.005112097,0.0008950415,0.0053160843,0.0024388153,0.0060920455,0.041488577],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027156675,0.00007921368,0.00023309591,0.00043874656,0.000023255088,0.00007020574,0.000029853121,0.00048367336,0.0006772983,0.0016245503,0.9089737,0.08733919],"study_design_scores_gemma":[0.000011523323,0.00007498667,0.0008863326,0.0002978828,0.00001950617,0.000315436,0.00004811038,0.001296285,0.0002726996,0.004301667,0.99244726,0.000028215525],"about_ca_topic_score_codex":0.00087538053,"about_ca_topic_score_gemma":0.0012387737,"teacher_disagreement_score":0.058975585,"about_ca_system_score_codex":0.0009508581,"about_ca_system_score_gemma":0.0015941246,"threshold_uncertainty_score":0.19729298},"labels":[],"label_agreement":null},{"id":"W2015973458","doi":"10.1287/inte.32.2.74.64","title":"How Should Team Captains Order Golfers on the Final Day of the Ryder Cup Matches?","year":2002,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada; Royal Ottawa Mental Health Centre","funders":"","keywords":"Order (exchange); SLATES; Advertising; Momentum (technical analysis); Engineering; Management; Operations research; Operations management; Marketing; Business; Computer science; Economics; World Wide Web; Finance","score_opus":0.08696453909582184,"score_gpt":0.2210731652860867,"score_spread":0.13410862619026487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015973458","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97213507,0.000067141336,0.0050468147,0.0020838233,0.00008429293,0.0001734582,0.00012776158,0.000039374485,0.020242263],"genre_scores_gemma":[0.9934836,0.00006156701,0.0027924462,0.00026191855,0.000014531525,0.00005749287,0.00007304649,0.000011299499,0.0032441],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985436,0.0007843403,0.000038587626,0.00018417275,0.00013677475,0.00031257127],"domain_scores_gemma":[0.99346644,0.0032685052,0.001062544,0.00022279884,0.0008752739,0.001104351],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027724272,0.00052405806,0.0005436593,0.0004373065,0.0012216957,0.002431831,0.0008974552,0.0020861211,0.0061138333],"category_scores_gemma":[0.01711133,0.00025186257,0.00030594863,0.00038117214,0.000750389,0.0015896328,0.00052580633,0.001407325,0.0013281173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0050056544,0.006333499,0.6583343,0.00047335395,0.0007459587,0.0010884774,0.009323969,0.07321221,0.011629558,0.049341153,0.033671387,0.1508404],"study_design_scores_gemma":[0.001241227,0.008350905,0.4292638,0.00023179238,0.0004397184,0.0004574335,0.06277093,0.364372,0.010422994,0.0831346,0.038858585,0.00045598936],"about_ca_topic_score_codex":0.021862932,"about_ca_topic_score_gemma":0.04193318,"teacher_disagreement_score":0.021862932,"about_ca_system_score_codex":0.0017934018,"about_ca_system_score_gemma":0.001788719,"threshold_uncertainty_score":0.043471336},"labels":[],"label_agreement":null},{"id":"W2019742604","doi":"10.1287/inte.30.1.96.11617","title":"An Asset and Liability Management System for Towers Perrin-Tillinghast","year":2000,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":95,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian General-Tower (Canada)","funders":"","keywords":"Liability; Asset (computer security); Pension; Actuarial science; Business; Plan (archaeology); Investment (military); Asset management; Generator (circuit theory); Finance; Risk management; Risk analysis (engineering); Computer science; Power (physics); Computer security","score_opus":0.015810974103581617,"score_gpt":0.296733585176161,"score_spread":0.2809226110725794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019742604","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08327718,0.00072235946,0.6287456,0.0018595273,0.00025574438,0.0009518391,0.008246257,0.19129762,0.08464391],"genre_scores_gemma":[0.5690908,0.0008413575,0.3118722,0.0004474004,0.0002517398,0.0008511579,0.017363777,0.0059132376,0.093368374],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99919695,0.00016950144,0.000064516564,0.00020406679,0.0003151823,0.00004975536],"domain_scores_gemma":[0.99818426,0.0005725912,0.00018438583,0.00039097332,0.00044721985,0.00022056818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016918167,0.00047476127,0.00038515948,0.0012239092,0.0005200439,0.0015673267,0.0009458989,0.0005714619,0.04265499],"category_scores_gemma":[0.004144773,0.00044290678,0.00032269914,0.00074648374,0.00021587718,0.0019015165,0.0012325458,0.00072790886,0.009523398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009975524,0.00047272412,0.012681384,0.00023513305,0.00008733957,0.0007928562,0.0007101541,0.078751564,0.014847381,0.029959613,0.22186644,0.6385978],"study_design_scores_gemma":[0.00024992842,0.00024484275,0.0056416695,0.00009332207,0.00006498599,0.00056488405,0.00011137663,0.66255724,0.011963152,0.01115565,0.307228,0.00012498346],"about_ca_topic_score_codex":0.004324331,"about_ca_topic_score_gemma":0.0033131863,"teacher_disagreement_score":0.04265499,"about_ca_system_score_codex":0.0010655827,"about_ca_system_score_gemma":0.0018100231,"threshold_uncertainty_score":0.14269519},"labels":[],"label_agreement":null},{"id":"W2025926540","doi":"10.1287/inte.1100.0525","title":"A Quarter of a Century of Academia–Industry Interfacing: The Alabama Productivity Center","year":2010,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Engineering Education and Curriculum Development","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Outreach; Quarter (Canadian coin); Center (category theory); Productivity; Interfacing; Public relations; Service (business); Tertiary sector of the economy; Engineering management; Marketing; Management; Engineering; Political science; Business; Economics; Economic growth","score_opus":0.007039499123187908,"score_gpt":0.22362755919410926,"score_spread":0.21658806007092135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025926540","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6711481,0.004890843,0.007827334,0.21358822,0.003135511,0.00011554581,0.00009369382,0.0006197889,0.09858099],"genre_scores_gemma":[0.89340883,0.0014612285,0.0034130688,0.012860356,0.0003155012,0.00006708733,0.00007470292,0.00023264442,0.08816656],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99630225,0.0013984895,0.000055398115,0.00032500556,0.0005371201,0.0013817841],"domain_scores_gemma":[0.99423015,0.0007137773,0.00026678471,0.0003654156,0.0008779209,0.0035459425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055080173,0.00045288168,0.00027137212,0.00070746226,0.025547378,0.015351806,0.0015447461,0.0036843768,0.012444723],"category_scores_gemma":[0.0053481036,0.00042107565,0.00023748036,0.00083726586,0.004897352,0.005932748,0.008950395,0.007697359,0.0016096008],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040434106,0.0017535753,0.03458564,0.00023979163,0.00006713443,0.0044287858,0.31150204,0.000999488,0.010150609,0.07304193,0.16589509,0.3969316],"study_design_scores_gemma":[0.000022416527,0.0003369257,0.012081373,0.00016734941,0.000016486138,0.00083194545,0.38784394,0.00064482,0.0017088923,0.005420004,0.5908533,0.000072629344],"about_ca_topic_score_codex":0.033958677,"about_ca_topic_score_gemma":0.08601099,"teacher_disagreement_score":0.033958677,"about_ca_system_score_codex":0.009017351,"about_ca_system_score_gemma":0.016930422,"threshold_uncertainty_score":0.06752205},"labels":[],"label_agreement":null},{"id":"W2027991041","doi":"10.1287/inte.1110.0594","title":"Introduction: 2010 Daniel H. Wagner Prize for Excellence in Operations Research Practice","year":2011,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Operations Management Techniques","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"IBM; Competition (biology); CLARITY; Excellence; Heuristics; Center of excellence; Operations research; Suite; Obsolescence; Watson; Operational excellence; Schedule; Computer science; Management; Marketing; Business; Engineering; Political science; Economics; Artificial intelligence","score_opus":0.29580409811915603,"score_gpt":0.45412619037885954,"score_spread":0.1583220922597035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027991041","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009679644,0.06603576,0.009697216,0.23413101,0.36899525,0.0002864329,0.0027218342,0.00087216095,0.3162924],"genre_scores_gemma":[0.013888808,0.062402338,0.0052453894,0.02776926,0.12582617,0.00027364455,0.0027757303,0.00096330914,0.7608553],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9945156,0.0005083265,0.0003803256,0.0008839357,0.0032017878,0.00050997816],"domain_scores_gemma":[0.98965234,0.0013051148,0.00047771158,0.00036176742,0.0059621627,0.0022409535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006402881,0.0020750398,0.0014383422,0.0026657905,0.0014456174,0.010738271,0.001655427,0.0050696773,0.14181614],"category_scores_gemma":[0.016211594,0.00054414966,0.00093663833,0.0022431326,0.0013403223,0.004497297,0.002666304,0.00545539,0.09514359],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001547242,0.000011954496,0.00004254654,0.000068332585,0.0000030999306,0.000011584949,0.000011782454,0.000092878974,0.000045417677,0.005580847,0.96520317,0.028912885],"study_design_scores_gemma":[0.000012222499,0.00002537616,0.0002875656,0.00030593982,0.0000033286722,0.000046446425,0.000029250765,0.0002723606,0.00007252294,0.005062517,0.99386674,0.000015734027],"about_ca_topic_score_codex":0.002808168,"about_ca_topic_score_gemma":0.0036570535,"teacher_disagreement_score":0.14181614,"about_ca_system_score_codex":0.006208572,"about_ca_system_score_gemma":0.005761028,"threshold_uncertainty_score":0.47442228},"labels":[],"label_agreement":null},{"id":"W2046076181","doi":"10.1287/inte.1070.0322","title":"Optimizing Highway Transportation at the United States Postal Service","year":2007,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Postal service; Service (business); Transport engineering; Business; Finance; Engineering; Marketing","score_opus":0.019345960917214966,"score_gpt":0.2791708987249374,"score_spread":0.2598249378077224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046076181","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7275554,0.0022325572,0.13573848,0.006829745,0.00028149885,0.0007758354,0.006094602,0.0014895549,0.11900231],"genre_scores_gemma":[0.95332456,0.0005265254,0.030108001,0.00016146564,0.0000335691,0.00012335886,0.0015929037,0.00013647057,0.013993204],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991978,0.00030564656,0.00002023904,0.00010450431,0.00016547155,0.00020640946],"domain_scores_gemma":[0.99941623,0.00015523416,0.00006276832,0.000029640578,0.00024493414,0.00009119002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008595179,0.0007178201,0.0005638771,0.0008957334,0.000870403,0.001808684,0.00061671674,0.00088969973,0.009412599],"category_scores_gemma":[0.0028716226,0.0003891156,0.00037222673,0.0013019509,0.00029427905,0.0011086114,0.0007598092,0.0006476556,0.0011237363],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018928615,0.00026477812,0.01439111,0.00010437336,0.000085402695,0.00014086877,0.000103131795,0.8395167,0.0012639341,0.015835477,0.04157408,0.08653093],"study_design_scores_gemma":[0.000029833165,0.00018116597,0.007356385,0.000023136161,0.000061648316,0.00003448748,0.00047054893,0.9733391,0.000784071,0.0065913787,0.011109405,0.000018898427],"about_ca_topic_score_codex":0.086696915,"about_ca_topic_score_gemma":0.104323976,"teacher_disagreement_score":0.086696915,"about_ca_system_score_codex":0.0033349267,"about_ca_system_score_gemma":0.005606736,"threshold_uncertainty_score":0.17238456},"labels":[],"label_agreement":null},{"id":"W2053134203","doi":"10.1287/inte.1090.0445","title":"Introduction: Applications of Management Science and Operations Research Models and Methods to Problems in Health Care","year":2009,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Health care; Management science; Queueing theory; Operations research; Health care delivery; Computer science; Affect (linguistics); Risk analysis (engineering); Engineering; Business; Economics; Psychology","score_opus":0.10820970897441509,"score_gpt":0.514470254749689,"score_spread":0.40626054577527393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053134203","genre_codex":"methods","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0047759926,0.10123766,0.57186973,0.16600886,0.04041519,0.00066257577,0.003729864,0.0013055785,0.10999457],"genre_scores_gemma":[0.07804376,0.19521348,0.49133703,0.052053325,0.08723905,0.0014887188,0.0024672786,0.00075194053,0.09140547],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9962721,0.0014978101,0.00028636603,0.00036341758,0.0014709817,0.00010932998],"domain_scores_gemma":[0.986925,0.010130306,0.0008059065,0.000488817,0.0013970092,0.0002529172],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00517351,0.000984376,0.0006010489,0.0021264157,0.00087027997,0.0039685434,0.0013366325,0.003306014,0.021852806],"category_scores_gemma":[0.015448657,0.00040087124,0.00095390837,0.0039833747,0.0016346128,0.003960118,0.0016572713,0.0047423383,0.008795098],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004950374,0.00011303833,0.0011237649,0.0023335237,0.000075064665,0.00017222157,0.00040825712,0.0075682737,0.0005682637,0.21021932,0.46812788,0.30924097],"study_design_scores_gemma":[0.00003513597,0.00007915974,0.0011405946,0.0011345589,0.000023621365,0.0004126849,0.00019095017,0.009695859,0.00043497936,0.2630341,0.72376096,0.00005740646],"about_ca_topic_score_codex":0.0012401757,"about_ca_topic_score_gemma":0.0011574753,"teacher_disagreement_score":0.021852806,"about_ca_system_score_codex":0.0010300212,"about_ca_system_score_gemma":0.0024918944,"threshold_uncertainty_score":0.07310498},"labels":[],"label_agreement":null},{"id":"W2056364446","doi":"10.1287/inte.30.3.95.11655","title":"Just-in-Time Manufacturing and Pollution Prevention Generate Mutual Benefits in the Furniture Industry","year":2000,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Environmental Sustainability in Business","field":"Business, Management and Accounting","cited_by":97,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Business; Control (management); Pollution prevention; Pollution; Production (economics); Investment (military); Work (physics); Environmental pollution; Manufacturing; Environmental economics; Industrial organization; Operations management; Marketing; Engineering; Environmental protection; Environmental science; Waste management; Economics; Management","score_opus":0.013739213167505173,"score_gpt":0.22032558360663326,"score_spread":0.2065863704391281,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056364446","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9706482,0.000457093,0.00085607654,0.004102587,0.00002357613,0.00001601732,0.000017557024,0.000013643699,0.023865202],"genre_scores_gemma":[0.9983543,0.00017075583,0.00031369744,0.00014422894,0.000009263425,0.0000039476668,0.000008940295,0.0000022496004,0.0009925689],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984823,0.0006907855,0.000032319844,0.0000905615,0.00034630098,0.00035774702],"domain_scores_gemma":[0.99600804,0.0015532688,0.00092315034,0.00023156506,0.0005003599,0.00078363676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001833915,0.00014804583,0.00015072571,0.0006822236,0.001587157,0.002420215,0.00024157848,0.00069771986,0.003601513],"category_scores_gemma":[0.0046571475,0.0001500543,0.00020927063,0.00069665315,0.0013550442,0.0014982554,0.0030565348,0.0006491653,0.0002655686],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008494699,0.0017027297,0.4718324,0.00049397285,0.00018329835,0.00085735595,0.0335492,0.0021746345,0.0113580795,0.0872159,0.00834412,0.38143885],"study_design_scores_gemma":[0.00006630823,0.00090225594,0.8677819,0.0002373371,0.00021688451,0.0003631917,0.04707536,0.0021071818,0.004128462,0.0331288,0.043918427,0.000073875875],"about_ca_topic_score_codex":0.0016628529,"about_ca_topic_score_gemma":0.0064261355,"teacher_disagreement_score":0.003601513,"about_ca_system_score_codex":0.0012619644,"about_ca_system_score_gemma":0.0018929149,"threshold_uncertainty_score":0.012048304},"labels":[],"label_agreement":null},{"id":"W2074009058","doi":"10.1287/inte.32.2.28.59","title":"In Search of Strategic Operations Research/Management Science","year":2002,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Competitive advantage; Strategic planning; Work (physics); Strategic management; Key (lock); Inclusion (mineral); Profit impact of marketing strategy; Business; Strategic information system; Strategic thinking; Strategic financial management; Knowledge management; Process management; Information system; Computer science; Engineering; Marketing; Management information systems; Chemistry","score_opus":0.25511617382513846,"score_gpt":0.37613531622006535,"score_spread":0.12101914239492689,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074009058","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020856963,0.08146964,0.06176877,0.33322904,0.00821323,0.00026919693,0.00092049106,0.00020070143,0.49307197],"genre_scores_gemma":[0.629824,0.16047163,0.075778425,0.067000255,0.015289826,0.00076958764,0.0028357825,0.00023666534,0.047793746],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9906783,0.004149589,0.0008354691,0.00078005437,0.0029792765,0.0005774241],"domain_scores_gemma":[0.97464925,0.014360939,0.0028785032,0.0021722943,0.0047337306,0.0012053429],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01565422,0.00089488673,0.0013322472,0.008620437,0.0031864282,0.0146596115,0.0014356251,0.004223207,0.019098775],"category_scores_gemma":[0.03338317,0.00039370882,0.000671036,0.01755793,0.008829848,0.016143804,0.00429119,0.0054487246,0.004993518],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025040912,0.000043729848,0.0010420667,0.0007925634,0.000023135086,0.00009719423,0.00088822417,0.0006354967,0.0001197962,0.90850663,0.032394294,0.055431835],"study_design_scores_gemma":[0.000019422512,0.00005627502,0.00090260647,0.0016015706,0.00001925461,0.00014190645,0.0041838163,0.0017079331,0.00025456076,0.67453706,0.31654903,0.000026575593],"about_ca_topic_score_codex":0.0040304926,"about_ca_topic_score_gemma":0.0040039825,"teacher_disagreement_score":0.019098775,"about_ca_system_score_codex":0.006231938,"about_ca_system_score_gemma":0.016372226,"threshold_uncertainty_score":0.08278841},"labels":[],"label_agreement":null},{"id":"W2083945967","doi":"10.1287/inte.1090.0444","title":"Rebuttal of “Polar Bear Population Forecasts: A Public-Policy Forecasting Audit”","year":2009,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Environment and Climate Change Canada","funders":"Office of Science; U.S. Forest Service; U.S. Geological Survey; Woods Hole Oceanographic Institution; Arctic Institute of North America; U.S. Department of Energy; National Science Foundation","keywords":"Population; Listing (finance); Audit; Rebuttal; Endangered species; Government (linguistics); Threatened species; Geography; Operations research; Political science; Business; Accounting; Ecology; Engineering; Habitat; Sociology; Finance; Law; Biology; Demography","score_opus":0.022039232329443968,"score_gpt":0.23342010357367826,"score_spread":0.2113808712442343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083945967","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034107063,0.0016562684,0.009652092,0.9118152,0.011781289,0.00032958295,0.0013729638,0.0013290169,0.02795642],"genre_scores_gemma":[0.5011404,0.005116479,0.029720962,0.41568178,0.010071131,0.000640131,0.0025840285,0.0010661599,0.0339791],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.8979504,0.021866584,0.011606279,0.0036564777,0.059367616,0.005552651],"domain_scores_gemma":[0.59905386,0.18375288,0.033737533,0.030546011,0.14568076,0.0072290073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.09914645,0.0008393148,0.00086576527,0.00522398,0.006880619,0.0110625625,0.0035399408,0.01588822,0.0026446322],"category_scores_gemma":[0.33653477,0.0015647039,0.00137641,0.005564149,0.005373679,0.0097947465,0.005084288,0.02910218,0.0018699444],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020246499,0.00019091718,0.012775058,0.0003808915,0.0000898541,0.0013874627,0.0063531217,0.003672286,0.0013761888,0.044947203,0.8309957,0.09762881],"study_design_scores_gemma":[0.0001245494,0.00021609258,0.016608251,0.0016692544,0.00020748744,0.00046158914,0.0056497543,0.016364148,0.0051344163,0.02950201,0.9236699,0.0003926605],"about_ca_topic_score_codex":0.059447855,"about_ca_topic_score_gemma":0.029203583,"teacher_disagreement_score":0.09914645,"about_ca_system_score_codex":0.013479977,"about_ca_system_score_gemma":0.055170856,"threshold_uncertainty_score":0.5243428},"labels":[],"label_agreement":null},{"id":"W2094427046","doi":"10.1287/inte.1070.0337","title":"Spreadsheet Model Helps to Assign Medical Residents at the University of Vermont's College of Medicine","year":2008,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Rotman School of Management, University of Toronto","keywords":"Scope (computer science); Scheduling (production processes); Computer science; Operations research; Software; Engineering management; Software engineering; Operations management; Engineering; Programming language","score_opus":0.11200069251111452,"score_gpt":0.3425552182805954,"score_spread":0.23055452576948085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094427046","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09116932,0.00012099562,0.8441623,0.0021383287,0.00021631435,0.00083395705,0.003155485,0.008146941,0.050056316],"genre_scores_gemma":[0.31172344,0.00032917826,0.6494201,0.00042063973,0.000056520923,0.00093792233,0.003252114,0.00094495225,0.03291515],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931455,0.00020397874,0.000050433708,0.00013761266,0.00022516695,0.00006833547],"domain_scores_gemma":[0.9974148,0.001350054,0.0002082235,0.0003037555,0.00059081503,0.0001323814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008974432,0.0008247257,0.00037515647,0.00074068457,0.00079379906,0.0014291363,0.0009634362,0.0007579644,0.015240526],"category_scores_gemma":[0.004410036,0.0004318301,0.0005354395,0.0008251467,0.00024162757,0.0015049422,0.0004826555,0.0010986306,0.0024657934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004827969,0.00061542395,0.0054556336,0.00018162116,0.000058559886,0.0002497901,0.00061902194,0.6930973,0.0068500666,0.05116616,0.043864284,0.19735922],"study_design_scores_gemma":[0.00009784043,0.00014065756,0.0010856705,0.0000749841,0.000031196167,0.000081409686,0.00014665221,0.9182166,0.005885121,0.015252132,0.05895133,0.00003642454],"about_ca_topic_score_codex":0.0151482895,"about_ca_topic_score_gemma":0.021392358,"teacher_disagreement_score":0.015240526,"about_ca_system_score_codex":0.0015205902,"about_ca_system_score_gemma":0.0038370576,"threshold_uncertainty_score":0.05098462},"labels":[],"label_agreement":null},{"id":"W2098734012","doi":"10.1287/inte.32.2.42.66","title":"Student Consulting Projects Benefit Faculty and Industry","year":2002,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Spreadsheets and End-User Computing","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"University of Calgary","keywords":"Engineering management; Engineering; Business; Knowledge management; Process management; Computer science","score_opus":0.055118753340031704,"score_gpt":0.2858808689916905,"score_spread":0.23076211565165883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098734012","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049669944,0.0025769563,0.023302663,0.10307516,0.0066002486,0.0013683698,0.0022172462,0.0074789333,0.80371046],"genre_scores_gemma":[0.12350518,0.0011506836,0.014996637,0.011862524,0.0024446456,0.00074761256,0.0015514902,0.0017604295,0.8419808],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.98635525,0.0036532679,0.0005883774,0.0010297669,0.006040777,0.0023325402],"domain_scores_gemma":[0.87934285,0.0053525176,0.0039216676,0.0063742525,0.034882158,0.07012658],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005672247,0.0013847722,0.0011272088,0.0027229295,0.0048609613,0.010312349,0.0014788749,0.0036640062,0.17314236],"category_scores_gemma":[0.034063537,0.0005622352,0.00054362766,0.0026197522,0.00093100587,0.0038922597,0.010340745,0.0024929552,0.13059708],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001079913,0.0008943816,0.0045322417,0.00007962254,0.000017431454,0.00031467597,0.0013898716,0.00022715268,0.0015126235,0.009954025,0.6453723,0.33559784],"study_design_scores_gemma":[0.000060183145,0.00029979637,0.0047566406,0.00006934103,0.000010557743,0.0007956409,0.0022672156,0.0007920419,0.0008687376,0.0066277813,0.9834245,0.000027623762],"about_ca_topic_score_codex":0.0008850136,"about_ca_topic_score_gemma":0.0033390454,"teacher_disagreement_score":0.17314236,"about_ca_system_score_codex":0.0021687702,"about_ca_system_score_gemma":0.008943287,"threshold_uncertainty_score":0.57921886},"labels":[],"label_agreement":null},{"id":"W2099087479","doi":"10.1287/inte.33.4.15.16372","title":"Early Detection of High-Risk Claims at the Workers' Compensation Board of British Columbia","year":2003,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Medical Malpractice and Liability Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; Workers Compensation Board of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Mitacs","keywords":"Workers' compensation; Compensation (psychology); Business; Actuarial science; Engineering; Psychology","score_opus":0.023769102386332133,"score_gpt":0.31946593347660296,"score_spread":0.29569683109027084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099087479","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9244141,0.0005193398,0.05697067,0.004249618,0.0000863324,0.00084823853,0.0019949316,0.00071187055,0.010204999],"genre_scores_gemma":[0.96684486,0.00018643706,0.02823197,0.00019526553,0.00002724763,0.00015123641,0.00080915284,0.000018811364,0.0035350246],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997095,0.0011271256,0.00023050344,0.00032020337,0.0007884815,0.00043864766],"domain_scores_gemma":[0.988139,0.0064334166,0.0011754122,0.00033221502,0.0032591731,0.0006608889],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003730444,0.00050356664,0.0004667651,0.0027750626,0.0010687119,0.0013234692,0.0010121752,0.00060267455,0.0026875623],"category_scores_gemma":[0.026058145,0.00029980062,0.00037203127,0.001791251,0.0003595059,0.0005377254,0.0009441574,0.0009958076,0.0006261196],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00068552454,0.0006167618,0.66251075,0.00019157531,0.00007607857,0.00078000204,0.0006220771,0.035878256,0.0018178396,0.0021994142,0.010881946,0.28373972],"study_design_scores_gemma":[0.00021065515,0.00033585992,0.35283905,0.0001873931,0.00010537836,0.00039133735,0.0008225708,0.62858933,0.004579449,0.004544709,0.0072831484,0.00011107418],"about_ca_topic_score_codex":0.391275,"about_ca_topic_score_gemma":0.42026672,"teacher_disagreement_score":0.608725,"about_ca_system_score_codex":0.003939426,"about_ca_system_score_gemma":0.008328131,"threshold_uncertainty_score":0.77799505},"labels":[],"label_agreement":null},{"id":"W2100639794","doi":"10.1287/inte.1050.0127","title":"A Florida County Locates Disaster Recovery Centers","year":2005,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":91,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Residence; Agency (philosophy); Emergency management; Mile; Transport engineering; Operations management; Engineering; Geography; Operations research; Business; Political science","score_opus":0.018808972725903362,"score_gpt":0.22096709783834945,"score_spread":0.20215812511244607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100639794","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9023739,0.00028832204,0.029686356,0.0031220808,0.00014271439,0.0005870458,0.006395067,0.0011576784,0.056246825],"genre_scores_gemma":[0.94432086,0.00015958474,0.042091273,0.00015811514,0.000020838572,0.0001374057,0.002798888,0.00003856438,0.010274581],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991924,0.0001749596,0.000016772345,0.00018101335,0.0002403938,0.0001944909],"domain_scores_gemma":[0.9985868,0.00025890622,0.00012817387,0.00010462632,0.0007355722,0.0001859431],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071973464,0.00045558857,0.00030478818,0.0015480401,0.0030310594,0.0015920936,0.0007009806,0.000992948,0.010620501],"category_scores_gemma":[0.0031547004,0.0003134616,0.0003483267,0.001586221,0.00040494563,0.0012712217,0.0011419137,0.00040997332,0.001245406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001984076,0.0010212032,0.28748065,0.00069952355,0.00015979083,0.0037433642,0.0048875012,0.1272014,0.014656716,0.037398905,0.16029026,0.36047667],"study_design_scores_gemma":[0.0004897712,0.0028768848,0.27335912,0.00049129507,0.00027386486,0.0025858749,0.023983313,0.3845214,0.015148083,0.009231049,0.28657556,0.00046372792],"about_ca_topic_score_codex":0.10835121,"about_ca_topic_score_gemma":0.21292578,"teacher_disagreement_score":0.10835121,"about_ca_system_score_codex":0.0032912488,"about_ca_system_score_gemma":0.0039408277,"threshold_uncertainty_score":0.21544105},"labels":[],"label_agreement":null},{"id":"W2101273286","doi":"10.1287/inte.1080.0405","title":"Fraser Health Uses Mathematical Programming to Plan Its Inpatient Hospital Network","year":2009,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Fraser Health; BC Cancer Agency","funders":"Fraser Health Authority","keywords":"Plan (archaeology); Process (computing); Population; Health care; Acute care; Operations management; Operations research; Capacity planning; Business; Computer science; Medicine; Engineering; Geography; Environmental health; Economics; Economic growth","score_opus":0.06127268751091639,"score_gpt":0.3935687067256145,"score_spread":0.3322960192146981,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101273286","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.060524072,0.0003333656,0.91677135,0.0020536797,0.000084742365,0.0006271779,0.0010045746,0.00046499062,0.01813607],"genre_scores_gemma":[0.46543473,0.00060350035,0.5233564,0.0003206273,0.00006644784,0.0011896656,0.0007899133,0.00012998522,0.00810873],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989728,0.0005414685,0.000038653536,0.00013010854,0.00014785047,0.0001690418],"domain_scores_gemma":[0.99599177,0.003300724,0.00024596264,0.00006402847,0.00024442168,0.0001530096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032399523,0.001513563,0.0011224198,0.0012633367,0.0010220133,0.0019605285,0.0013323912,0.0012095597,0.0050869007],"category_scores_gemma":[0.005137137,0.0010818148,0.0012002067,0.0013997117,0.0009198157,0.0011276326,0.0011807054,0.0017139658,0.0004611896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025741754,0.000025156649,0.00030583102,0.000019951152,0.000014503605,0.000025757987,0.000020380947,0.9864476,0.000054721317,0.008601593,0.0006846718,0.00377407],"study_design_scores_gemma":[0.000011920203,0.000014998541,0.000033303688,0.000003847843,0.000003917894,0.0000041701387,0.000017453103,0.99578863,0.000056204557,0.003636915,0.00042520452,0.000003523575],"about_ca_topic_score_codex":0.047340296,"about_ca_topic_score_gemma":0.044291858,"teacher_disagreement_score":0.9956592,"about_ca_system_score_codex":0.0043408195,"about_ca_system_score_gemma":0.0057319994,"threshold_uncertainty_score":0.0941295},"labels":[],"label_agreement":null},{"id":"W2106360850","doi":"10.1287/inte.1120.0650","title":"Ford Motor Company Implements Integrated Planning and Scheduling in a Complex Automotive Manufacturing Environment","year":2012,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Automotive industry; Scheduling (production processes); Stamping; Manufacturing engineering; Production planning; Supply chain; Engineering; Overtime; Industrial engineering; Operations research; Operations management; Business; Production (economics); Marketing; Economics","score_opus":0.027610855958282308,"score_gpt":0.2549771217926849,"score_spread":0.2273662658344026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106360850","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15440631,0.00048511033,0.6990671,0.00045111336,0.0002118633,0.0007645756,0.002148184,0.09469708,0.047768686],"genre_scores_gemma":[0.4696373,0.0002429369,0.5071787,0.00012313215,0.00003277084,0.00025274066,0.0029190944,0.0014970412,0.018116293],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9994367,0.00007131284,0.00002763629,0.00019207186,0.00016516689,0.000107108805],"domain_scores_gemma":[0.99897134,0.00032109793,0.000059865342,0.00022997304,0.0003088443,0.000108924534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008760814,0.0008863114,0.00039131704,0.0006232552,0.0005564319,0.000906402,0.0008636655,0.00041262168,0.009291849],"category_scores_gemma":[0.0015811168,0.0005100172,0.00033516382,0.0006772278,0.0002732143,0.0006347761,0.0005957823,0.0005335535,0.0019789387],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00093252567,0.00071328954,0.013092256,0.00022967272,0.00011482109,0.0002337093,0.00031583707,0.18425514,0.019238787,0.008617937,0.048023555,0.72423255],"study_design_scores_gemma":[0.00038092912,0.00036425638,0.0055756,0.000043755368,0.000060808998,0.000132327,0.00011017684,0.8562501,0.031469844,0.0029559336,0.10257105,0.00008521117],"about_ca_topic_score_codex":0.04315776,"about_ca_topic_score_gemma":0.04600855,"teacher_disagreement_score":0.04315776,"about_ca_system_score_codex":0.0013319827,"about_ca_system_score_gemma":0.0033219226,"threshold_uncertainty_score":0.085813105},"labels":[],"label_agreement":null},{"id":"W2109092812","doi":"10.1287/inte.1050.0194","title":"The University of Toronto’s Rotman School of Management Uses Management Science to Create MBA Study Groups","year":2006,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Management and Marketing Education","field":"Business, Management and Accounting","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Work (physics); Group (periodic table); Working group; Process (computing); Mathematics education; Engineering management; Computer science; Management; Engineering; Psychology","score_opus":0.008498257883819513,"score_gpt":0.2199077129801811,"score_spread":0.2114094550963616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109092812","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09305661,0.0071761594,0.08887353,0.03268836,0.0028878513,0.0025243897,0.004483524,0.016511787,0.75179774],"genre_scores_gemma":[0.23948225,0.0053672376,0.14989991,0.0017706633,0.00065161934,0.0009466743,0.0024023994,0.0019252279,0.59755397],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.997044,0.00056422123,0.00015784953,0.0005363062,0.0011868344,0.0005108042],"domain_scores_gemma":[0.9857759,0.0011712317,0.00071622524,0.0015958103,0.0031582944,0.0075825313],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004079959,0.0008329318,0.0005413755,0.0034453673,0.006019535,0.004536883,0.0012811902,0.0008921216,0.08056591],"category_scores_gemma":[0.0073070205,0.0009872415,0.00042652,0.002972482,0.0021607217,0.0013159973,0.0029100373,0.0012235064,0.014390226],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023289157,0.0004778579,0.019453596,0.00023810155,0.000020410731,0.00021585276,0.004044552,0.0009637586,0.0037089086,0.029799772,0.48596466,0.45487964],"study_design_scores_gemma":[0.000105490435,0.000265075,0.03103075,0.00012968261,0.000013219351,0.000090689886,0.0010547884,0.0013520308,0.0017258147,0.0030286722,0.96114486,0.000058834452],"about_ca_topic_score_codex":0.2203072,"about_ca_topic_score_gemma":0.53595006,"teacher_disagreement_score":0.99592006,"about_ca_system_score_codex":0.0119381845,"about_ca_system_score_gemma":0.02251493,"threshold_uncertainty_score":0.43804973},"labels":[],"label_agreement":null},{"id":"W2113108023","doi":"10.1287/inte.32.4.28.54","title":"Implementing a Distribution-Network Decision-Support System at Pfizer/Warner-Lambert","year":2002,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Decision support system; Plan (archaeology); Operations research; Supply chain; Computer science; Operations management; Distribution (mathematics); Process management; Business; Engineering; Marketing; Artificial intelligence; Mathematics","score_opus":0.04395180645594679,"score_gpt":0.26697503864329386,"score_spread":0.22302323218734707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113108023","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2873262,0.0005447063,0.56159514,0.006563457,0.00044756776,0.0024595745,0.005979836,0.06009066,0.074992865],"genre_scores_gemma":[0.6250229,0.00037617347,0.3487382,0.0004007051,0.00014050383,0.0005808658,0.004442301,0.0009490366,0.01934924],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.997985,0.0006334352,0.00012342074,0.00048504444,0.00050275744,0.00027041713],"domain_scores_gemma":[0.9957569,0.0018499608,0.00024042693,0.0004897978,0.0010885984,0.00057428435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004066608,0.0006308288,0.0005271811,0.0014732876,0.0010885602,0.0025468268,0.0015164217,0.000711904,0.017463336],"category_scores_gemma":[0.006733381,0.0004411566,0.00025965562,0.0013627808,0.0004078479,0.0028769935,0.0010637322,0.0010170508,0.0035118156],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023270845,0.0014309944,0.019193642,0.00026439084,0.00012012739,0.000990333,0.000991277,0.15941319,0.017002393,0.016296452,0.07545476,0.7065154],"study_design_scores_gemma":[0.0008047296,0.0004353213,0.004005023,0.00011066915,0.000103280414,0.00017852045,0.00055821444,0.82729286,0.031042125,0.009695832,0.12559423,0.00017925455],"about_ca_topic_score_codex":0.013670987,"about_ca_topic_score_gemma":0.008112785,"teacher_disagreement_score":0.017463336,"about_ca_system_score_codex":0.002572392,"about_ca_system_score_gemma":0.004097436,"threshold_uncertainty_score":0.058420658},"labels":[],"label_agreement":null},{"id":"W2118867130","doi":"10.1287/inte.1050.0154","title":"Scheduling Employees in Quebec’s Liquor Stores with Integer Programming","year":2005,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Corporation; Scheduling (production processes); Integer programming; Schedule; Operations research; Computer science; Operations management; Business; Database; Engineering; Operating system; Finance","score_opus":0.06282176912898277,"score_gpt":0.35011510874133606,"score_spread":0.28729333961235326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118867130","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6833928,0.00094250066,0.24868245,0.0021379802,0.00012144199,0.001066233,0.0029938256,0.0013922469,0.05927049],"genre_scores_gemma":[0.8436883,0.00048205082,0.13874933,0.0002216964,0.000035785757,0.00028663586,0.0017151593,0.00014701867,0.014673986],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945813,0.00016634875,0.000020209052,0.00008150309,0.00007336239,0.00020041259],"domain_scores_gemma":[0.9989912,0.00059772516,0.00010016258,0.00003394076,0.00015496953,0.000122040175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001227346,0.00084358355,0.0005101422,0.0008499277,0.0009189463,0.0020997259,0.00094385527,0.00068228046,0.0059698],"category_scores_gemma":[0.002042754,0.0005335934,0.00044775612,0.001293134,0.0004836134,0.0006903513,0.00041894842,0.0006837353,0.00048700755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021683463,0.00017762963,0.0025419423,0.000091015434,0.00002064961,0.00010589578,0.00014063538,0.9494023,0.0008523292,0.0043954137,0.0046216827,0.037433695],"study_design_scores_gemma":[0.00004879551,0.000064456406,0.00096750987,0.000012268201,0.000012096468,0.000010660852,0.00016863864,0.99439913,0.00044888424,0.0013553287,0.0025020926,0.00001010398],"about_ca_topic_score_codex":0.44678536,"about_ca_topic_score_gemma":0.53085834,"teacher_disagreement_score":0.55321467,"about_ca_system_score_codex":0.006317192,"about_ca_system_score_gemma":0.008476562,"threshold_uncertainty_score":0.88836956},"labels":[],"label_agreement":null},{"id":"W2119849184","doi":"10.1287/inte.30.2.54.11677","title":"TransAlta Redesigns Its Service-Delivery Network","year":2000,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"TransAlta (Canada); University of Alberta","funders":"","keywords":"Staffing; Service (business); Heuristics; Service delivery framework; Operations management; Operations research; Business; Engineering; Transport engineering; Computer science; Marketing","score_opus":0.022148449344022318,"score_gpt":0.24065371943035052,"score_spread":0.2185052700863282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119849184","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29337755,0.0011941727,0.4647179,0.015254365,0.002282738,0.0029917005,0.0055993637,0.032690905,0.18189126],"genre_scores_gemma":[0.5754766,0.0007993102,0.33471385,0.001769585,0.0001923285,0.0006087284,0.006332624,0.0011598805,0.07894701],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982016,0.00041751127,0.00006286793,0.000262302,0.00069028256,0.00036542647],"domain_scores_gemma":[0.99637765,0.0004516174,0.00015453594,0.0004418871,0.0021281792,0.00044620995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019901472,0.00065794267,0.00038212794,0.0011067985,0.0013649844,0.0023023828,0.0013285999,0.00087194785,0.007502102],"category_scores_gemma":[0.005363469,0.00029666675,0.0003848844,0.0015888588,0.0004304824,0.0019693288,0.0010509903,0.0015508854,0.0030004936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073710416,0.0007720897,0.015687358,0.00017047998,0.00006188158,0.00029647027,0.00054926856,0.11127807,0.013267905,0.0339164,0.17303638,0.65022653],"study_design_scores_gemma":[0.00024273373,0.00045177262,0.0084901,0.000072128445,0.00008023528,0.00034141404,0.0007893619,0.5580032,0.011101456,0.005716464,0.41458932,0.00012177881],"about_ca_topic_score_codex":0.37727866,"about_ca_topic_score_gemma":0.3865153,"teacher_disagreement_score":0.37727866,"about_ca_system_score_codex":0.007667551,"about_ca_system_score_gemma":0.013796675,"threshold_uncertainty_score":0.7501653},"labels":[],"label_agreement":null},{"id":"W2120218454","doi":"10.1287/inte.1100.0510","title":"Approximate Dynamic Programming Captures Fleet Operations for Schneider National","year":2010,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Operations research; Fleet management; Quality (philosophy); Service (business); Dynamic programming; Computer science; Operations management; Engineering; Transport engineering; Business; Marketing","score_opus":0.012657447136643293,"score_gpt":0.2662540256432108,"score_spread":0.2535965785065675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120218454","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79053307,0.00014423726,0.17094389,0.00088234525,0.000039769107,0.000116325,0.0036252723,0.00046825444,0.033246778],"genre_scores_gemma":[0.98247176,0.00007529423,0.010579255,0.000034624034,0.0000060307834,0.00006140111,0.0010215937,0.000043964414,0.0057062143],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997631,0.00005923122,0.000009424414,0.00006278729,0.000035106157,0.000070351765],"domain_scores_gemma":[0.9993104,0.00040717685,0.000074826676,0.000043030403,0.00011305108,0.000051510375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005400013,0.00060215004,0.0004478741,0.0005061667,0.00049140415,0.00095749635,0.0006932972,0.0010316471,0.0044669253],"category_scores_gemma":[0.002180769,0.0005015337,0.000540533,0.0007644705,0.00048180678,0.0012046592,0.00041180156,0.0007882437,0.00042088705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009860881,0.0000042628913,0.00036912947,0.0000024492524,0.000002070569,0.0000089959785,0.0000068050945,0.9975726,0.000042377986,0.0012209995,0.00016483507,0.00059559906],"study_design_scores_gemma":[0.000001971529,0.0000044554467,0.00018142234,0.0000010817292,0.000001226838,0.0000022386073,0.00000951413,0.99901855,0.000036183737,0.0005479473,0.00019325904,0.0000021462386],"about_ca_topic_score_codex":0.19047631,"about_ca_topic_score_gemma":0.11592915,"teacher_disagreement_score":0.19047631,"about_ca_system_score_codex":0.003500618,"about_ca_system_score_gemma":0.0022345507,"threshold_uncertainty_score":0.37873518},"labels":[],"label_agreement":null},{"id":"W2124194632","doi":"10.1287/inte.1100.0550","title":"A Nonhomogeneous Agent-Based Simulation Approach to Modeling the Spread of Disease in a Pandemic Outbreak","year":2011,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Outbreak; Pandemic; Disease; Transmission (telecommunications); Promotion (chess); Population; Agency (philosophy); Operations research; Computer science; Geography; Environmental health; Risk analysis (engineering); Business; Coronavirus disease 2019 (COVID-19); Medicine; Infectious disease (medical specialty); Virology; Engineering; Telecommunications; Political science","score_opus":0.2822713010076148,"score_gpt":0.38235906921112695,"score_spread":0.10008776820351212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124194632","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28330815,0.0006086633,0.6855164,0.003212892,0.00021341135,0.00032745348,0.0012645356,0.00046671866,0.025081793],"genre_scores_gemma":[0.93928313,0.00062026974,0.05021254,0.00014851788,0.000075293196,0.00034083863,0.00044014637,0.00004649096,0.008832874],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942315,0.00034421167,0.00003083186,0.00007666876,0.0000625207,0.000062605075],"domain_scores_gemma":[0.9985812,0.00094587397,0.00014910163,0.000058948594,0.00013022708,0.00013467885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010064456,0.00071435334,0.00081885967,0.00084647414,0.0009866887,0.0014304515,0.0016101811,0.0017080747,0.0028960481],"category_scores_gemma":[0.003249239,0.00054844475,0.0010698263,0.0009439209,0.0010734602,0.0011437257,0.0012564654,0.001174278,0.00027171386],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000173898,0.000016324571,0.00069154345,0.000007452866,0.000014359228,0.00003432866,0.000031144835,0.99288964,0.0000818472,0.0054732594,0.00011908459,0.00062356814],"study_design_scores_gemma":[0.000010726077,0.000009864754,0.00010841966,0.0000022796944,0.00000539642,0.0000046506743,0.000014587226,0.997482,0.000024432991,0.0020819157,0.00025206598,0.0000036290262],"about_ca_topic_score_codex":0.049193323,"about_ca_topic_score_gemma":0.028386414,"teacher_disagreement_score":0.049193323,"about_ca_system_score_codex":0.0017228713,"about_ca_system_score_gemma":0.0019797864,"threshold_uncertainty_score":0.097813964},"labels":[],"label_agreement":null},{"id":"W2131427758","doi":"10.1287/inte.1090.0435","title":"A Simulation Model to Compare Strategies for the Reduction of Health-Care–Associated Infections","year":2009,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Isolation (microbiology); Hygiene; Infection control; Health care; Discrete event simulation; Medicine; Operations management; Medical emergency; Business; Operations research; Computer science; Intensive care medicine; Economics; Engineering; Simulation; Economic growth","score_opus":0.12066629367792,"score_gpt":0.45519526300400587,"score_spread":0.3345289693260859,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131427758","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6904087,0.0010506386,0.2628441,0.0040546735,0.00044336103,0.0008467199,0.004039101,0.0007573704,0.035555284],"genre_scores_gemma":[0.9722152,0.0003984739,0.022660363,0.00018803665,0.000036636342,0.00046641534,0.0008855745,0.00003290365,0.0031164212],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893385,0.0006655837,0.000043436976,0.000094124356,0.00009488294,0.00016807637],"domain_scores_gemma":[0.9922497,0.0063318373,0.0003636781,0.00018261108,0.000456128,0.00041606446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002529798,0.0011192353,0.0012012052,0.0011706761,0.0007143782,0.0014055282,0.0014384832,0.0019493252,0.0055615823],"category_scores_gemma":[0.00852793,0.0005802106,0.0010928503,0.0009987663,0.0006394065,0.0011982459,0.00097643177,0.0014396379,0.0003221698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000100553516,0.00007265483,0.0006899264,0.00001351974,0.000025565148,0.000013326978,0.000008803631,0.99629456,0.00005360855,0.0016267968,0.0002501318,0.00085054094],"study_design_scores_gemma":[0.000048211536,0.000060064238,0.00015459003,0.000003874118,0.000012816288,0.0000031109591,0.000011559871,0.9986512,0.00003655982,0.0008056112,0.00020811471,0.000004274315],"about_ca_topic_score_codex":0.035435405,"about_ca_topic_score_gemma":0.015647108,"teacher_disagreement_score":0.035435405,"about_ca_system_score_codex":0.0028772221,"about_ca_system_score_gemma":0.0032607613,"threshold_uncertainty_score":0.07045829},"labels":[],"label_agreement":null},{"id":"W2134421244","doi":"10.1287/inte.1040.0067","title":"General Motors Optimizes Its Scheduling of Cold-Weather Tests","year":2004,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"General Motors (Canada)","funders":"Oregon State University","keywords":"Warranty; Scheduling (production processes); Schedule; Operations research; Cold weather; Engineering; General motors; Computer science; Automotive engineering; Transport engineering; Operations management; Operating system","score_opus":0.023779067967838047,"score_gpt":0.28469505830260505,"score_spread":0.260915990334767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134421244","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.603772,0.00073608005,0.2729128,0.0011013753,0.0003302604,0.0005723415,0.002318924,0.011035359,0.10722085],"genre_scores_gemma":[0.8923351,0.00011501029,0.09354026,0.00012096906,0.00003552802,0.00010359156,0.0009077388,0.0003735691,0.012468163],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993722,0.00016998853,0.000015206685,0.00012101561,0.0001226043,0.00019893925],"domain_scores_gemma":[0.9991716,0.00033137575,0.00008895531,0.000094846175,0.00019424845,0.00011888855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081604026,0.0010047536,0.00063955097,0.0006348251,0.000436737,0.0007794292,0.0009532202,0.00055294303,0.0070739803],"category_scores_gemma":[0.002131217,0.00037404016,0.00040136988,0.0006595181,0.00035542896,0.00045800017,0.0003322408,0.00053852535,0.0010734254],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055553863,0.00020127001,0.003027039,0.0000941027,0.000048263682,0.000097174234,0.000039457354,0.8632733,0.0043367697,0.0037135838,0.01731664,0.107296854],"study_design_scores_gemma":[0.00007271053,0.00016506307,0.0010920085,0.0000051524758,0.000019903126,0.000021777283,0.000039508963,0.98881626,0.0023072336,0.0012689283,0.006181589,0.000009833106],"about_ca_topic_score_codex":0.026417062,"about_ca_topic_score_gemma":0.033966184,"teacher_disagreement_score":0.026417062,"about_ca_system_score_codex":0.0018361002,"about_ca_system_score_gemma":0.0024771611,"threshold_uncertainty_score":0.052526653},"labels":[],"label_agreement":null},{"id":"W2139457845","doi":"10.1287/inte.1040.0097","title":"Improving Volunteer Scheduling for the Edmonton Folk Festival","year":2004,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Crew; Entertainment; Advertising; Scheduling (production processes); Operations management; Business; Operations research; Marketing; Psychology; Engineering; Aeronautics; Art; Visual arts","score_opus":0.08812373420240385,"score_gpt":0.35863292571073196,"score_spread":0.2705091915083281,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139457845","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7786161,0.00022465587,0.21065925,0.00043270944,0.00007948576,0.00060752296,0.00058196305,0.0017557219,0.007042697],"genre_scores_gemma":[0.76033515,0.00015958956,0.23502316,0.0000391652,0.000020727333,0.00023366467,0.00080959016,0.0002205112,0.0031583852],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99950194,0.00021329637,0.000028457287,0.00009477986,0.00007979689,0.000081624894],"domain_scores_gemma":[0.99797064,0.0011245385,0.00017956804,0.00015305285,0.00028214586,0.00029001455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002451726,0.00047697395,0.00032911662,0.0006753619,0.0006883318,0.00088450685,0.0006910445,0.0002918068,0.0029692804],"category_scores_gemma":[0.00476056,0.00028563637,0.00029707546,0.0006294055,0.00019444327,0.0005570634,0.0004502063,0.00036268358,0.0003414944],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010680186,0.0008453055,0.012407856,0.00028236632,0.00004001851,0.00028300565,0.001624109,0.5420561,0.016404849,0.007960731,0.011772735,0.40525487],"study_design_scores_gemma":[0.00021382443,0.00065761706,0.005170418,0.00003136364,0.0000405768,0.000067080124,0.00086631405,0.9604133,0.011405879,0.004901003,0.016193308,0.000039236453],"about_ca_topic_score_codex":0.011571712,"about_ca_topic_score_gemma":0.021134641,"teacher_disagreement_score":0.011571712,"about_ca_system_score_codex":0.001083626,"about_ca_system_score_gemma":0.00267759,"threshold_uncertainty_score":0.023008704},"labels":[],"label_agreement":null},{"id":"W2143105265","doi":"10.1287/inte.2013.0683","title":"Mathematical Programming Guides Air-Ambulance Routing at Ornge","year":2013,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Operations research; Work (physics); Computer science; Fixed wing; Routing (electronic design automation); Route planning; Air traffic control; Range (aeronautics); Vehicle routing problem; Operations management; Aeronautics; Transport engineering; Engineering; Computer network; Wing","score_opus":0.018716778310650772,"score_gpt":0.2584463641114855,"score_spread":0.23972958580083475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143105265","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025632274,0.00044479963,0.95439583,0.002503466,0.00009184006,0.00009660842,0.00043041146,0.00062368036,0.038850043],"genre_scores_gemma":[0.08266805,0.001935067,0.8810272,0.00035245012,0.000101432575,0.00025083672,0.0005852234,0.00057912606,0.032500584],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998979,0.00044958142,0.000040131672,0.00013015057,0.0003190555,0.00008215259],"domain_scores_gemma":[0.99852955,0.00092832453,0.000113399255,0.000087766144,0.00029376356,0.00004713625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017475762,0.0013099031,0.00068193336,0.0009632821,0.001220143,0.0026265238,0.0013348559,0.0008777839,0.018739086],"category_scores_gemma":[0.0049263844,0.00089559646,0.0005867727,0.0016780708,0.0010588035,0.0017488818,0.0009411447,0.001992523,0.0042769616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003794558,0.000058879206,0.00077989296,0.00020962147,0.000017153448,0.00016287534,0.00031201012,0.50299233,0.002269236,0.28054842,0.045984473,0.1666271],"study_design_scores_gemma":[0.000020607342,0.000022026921,0.00027984308,0.00009925401,0.00000725994,0.00006150708,0.0002205617,0.77497375,0.00094939844,0.09329369,0.13004339,0.000028708748],"about_ca_topic_score_codex":0.12171789,"about_ca_topic_score_gemma":0.232816,"teacher_disagreement_score":0.8782821,"about_ca_system_score_codex":0.0052313623,"about_ca_system_score_gemma":0.008289226,"threshold_uncertainty_score":0.24201882},"labels":[],"label_agreement":null},{"id":"W2146336822","doi":"10.1287/inte.1110.0583","title":"Universal Tool for Vaccine Scheduling: Applications for Children and Adults","year":2011,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Oak Ridge Institute for Science and Education; Centers for Disease Control and Prevention; Georgia Institute of Technology; U.S. Department of Energy","keywords":"Schedule; Vaccination; Immunization; Scheduling (production processes); Computer science; Disease control; Medicine; Disease; Health care; Operations research; Environmental health; Operations management; Engineering; Immunology; Political science","score_opus":0.021082069023598916,"score_gpt":0.2738359357310502,"score_spread":0.25275386670745126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146336822","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032652993,0.0020871388,0.6670437,0.002126023,0.00041040278,0.001091797,0.021621797,0.2559898,0.016976364],"genre_scores_gemma":[0.18056785,0.0015619873,0.7908641,0.0007309028,0.00014697848,0.0014742201,0.013722419,0.004593174,0.0063383533],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988279,0.00033083395,0.0002284672,0.00020538186,0.00032536552,0.00008202338],"domain_scores_gemma":[0.993565,0.004365134,0.0005077153,0.00047569105,0.0007500833,0.00033631807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028688319,0.001239764,0.00085302535,0.002588878,0.000468431,0.0010079329,0.0016249206,0.0010368915,0.02670298],"category_scores_gemma":[0.017425723,0.0006322333,0.00076600764,0.0020822217,0.00024206475,0.0019473204,0.0015843366,0.0008533713,0.005047945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00088070164,0.00047138138,0.02057421,0.0011775609,0.00017434426,0.00056805625,0.0008012482,0.0216527,0.0028074025,0.011149901,0.12596363,0.8137788],"study_design_scores_gemma":[0.00092149526,0.0005594076,0.016642202,0.0013284028,0.00022226572,0.001638937,0.00082172436,0.514036,0.014434258,0.051393297,0.39766422,0.00033781346],"about_ca_topic_score_codex":0.004938808,"about_ca_topic_score_gemma":0.0056115715,"teacher_disagreement_score":0.02670298,"about_ca_system_score_codex":0.0006438942,"about_ca_system_score_gemma":0.001494532,"threshold_uncertainty_score":0.089330316},"labels":[],"label_agreement":null},{"id":"W2147714773","doi":"10.1287/inte.1100.0520","title":"Taking the Politics Out of Paving: Achieving Transportation Asset Management Excellence Through OR","year":2011,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Government of New Brunswick; Transport Canada","funders":"U.S. Department of Transportation","keywords":"Asset management; Asset (computer security); Business; Heuristic; Operations research; Transport engineering; Finance; Computer science; Engineering; Computer security","score_opus":0.20771048777770518,"score_gpt":0.372130339538934,"score_spread":0.1644198517612288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147714773","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.089256905,0.0055050463,0.10196193,0.04356338,0.00039318713,0.00027643412,0.00017983674,0.00051792664,0.7583454],"genre_scores_gemma":[0.86895,0.0070016286,0.06453795,0.0031536235,0.00013534242,0.00009961932,0.00022944837,0.00018904387,0.05570325],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996223,0.0016305964,0.00008992693,0.0002515054,0.0008053994,0.0009995408],"domain_scores_gemma":[0.9986602,0.00022061213,0.00019470642,0.0002131757,0.00038849976,0.00032281593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004269236,0.00047322665,0.00031773563,0.0011642749,0.0023778952,0.009990015,0.0012391638,0.0008284311,0.0076933713],"category_scores_gemma":[0.0041852593,0.00018474105,0.0002957501,0.0019964306,0.003341814,0.006813734,0.0046308804,0.001001614,0.0013541443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006996026,0.00012209422,0.0049024886,0.00022915888,0.00003383241,0.00016564387,0.0018181275,0.009861294,0.0008780235,0.64575565,0.028095573,0.30806813],"study_design_scores_gemma":[0.000033246444,0.00013636294,0.006175517,0.00074753264,0.000068836016,0.00017669662,0.013796837,0.019417768,0.0022710592,0.36722457,0.5898947,0.00005688547],"about_ca_topic_score_codex":0.032022446,"about_ca_topic_score_gemma":0.07729831,"teacher_disagreement_score":0.032022446,"about_ca_system_score_codex":0.0071757436,"about_ca_system_score_gemma":0.015351748,"threshold_uncertainty_score":0.063672125},"labels":[],"label_agreement":null},{"id":"W2149852331","doi":"10.1287/inte.1040.0113","title":"Bombardier Flexjet Significantly Improves Its Fractional Aircraft Ownership Operations","year":2005,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Crew; Charter; Engineering; Aeronautics; Operations research; Service (business); Operations management; Business; Marketing","score_opus":0.022731258156740753,"score_gpt":0.2711719378261229,"score_spread":0.24844067966938216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149852331","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82568556,0.0006992484,0.087058276,0.0010490882,0.00016070447,0.00012609869,0.0006559578,0.0056121415,0.07895289],"genre_scores_gemma":[0.9425383,0.00027095273,0.040152226,0.00012140392,0.00002068143,0.000020973364,0.00058762915,0.00027753031,0.016010294],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997204,0.00003274212,0.000009551208,0.00004174956,0.00013512225,0.000060458766],"domain_scores_gemma":[0.9997472,0.00005557896,0.000027342014,0.00005586912,0.00007617703,0.000037825437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050361606,0.0005520649,0.00029577827,0.00053847505,0.0003321768,0.0009940374,0.0003888686,0.0003286156,0.00546983],"category_scores_gemma":[0.0010724805,0.00011191402,0.00024606858,0.00051483436,0.00022230927,0.0010609952,0.00054814655,0.00046451407,0.00087536726],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087309553,0.0005980143,0.008562855,0.00010094186,0.000041029503,0.00020128497,0.00012910414,0.17668973,0.056869414,0.012419165,0.0148429815,0.7286724],"study_design_scores_gemma":[0.0002275414,0.0024073387,0.026325108,0.000054919175,0.00009047554,0.0005316402,0.000292412,0.68686116,0.14800954,0.006628467,0.12849426,0.00007709921],"about_ca_topic_score_codex":0.007750405,"about_ca_topic_score_gemma":0.006618894,"teacher_disagreement_score":0.007750405,"about_ca_system_score_codex":0.00078216876,"about_ca_system_score_gemma":0.00091118354,"threshold_uncertainty_score":0.018298388},"labels":[],"label_agreement":null},{"id":"W2150863986","doi":"10.1287/inte.31.3.3.9636","title":"Value Analysis and Optimization of Reusable Containers at Canada Post","year":2001,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Supply chain; Container (type theory); Stock (firearms); Business; Operations research; Productivity; Stock control; Operations management; Inventory control; Control (management); Environmental economics; Computer science; Industrial organization; Marketing; Economics; Engineering","score_opus":0.00953963887279685,"score_gpt":0.19714735458446916,"score_spread":0.1876077157116723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150863986","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96992797,0.00021083145,0.024451548,0.00017287665,0.0000108007935,0.000071219474,0.0007373623,0.00014372672,0.004273674],"genre_scores_gemma":[0.98699355,0.00007601,0.0113615785,0.0000073089423,0.0000019261886,0.00002717954,0.00035413375,0.000042916214,0.0011354651],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9993691,0.00012337827,0.00001882316,0.000081881364,0.00014946566,0.00025734238],"domain_scores_gemma":[0.998276,0.00081375556,0.00020810061,0.0001164601,0.0004505625,0.00013515163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012319596,0.0007860127,0.0005797084,0.001640051,0.0008587427,0.0016558219,0.001035953,0.0006859184,0.002578237],"category_scores_gemma":[0.0038626406,0.0005662849,0.0007837815,0.0024231246,0.0009900734,0.0013018332,0.00063821836,0.00052534696,0.00011415221],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002731562,0.00008166111,0.014352219,0.00007851654,0.000038084054,0.00019918551,0.0001619589,0.944545,0.0027719757,0.0101727415,0.0010037655,0.026321841],"study_design_scores_gemma":[0.000017583303,0.00010397867,0.00923071,0.00001554869,0.000040240408,0.000022323293,0.00029770355,0.9804105,0.0034521306,0.00507463,0.0012974666,0.000037162314],"about_ca_topic_score_codex":0.2932191,"about_ca_topic_score_gemma":0.28883797,"teacher_disagreement_score":0.7067809,"about_ca_system_score_codex":0.010603369,"about_ca_system_score_gemma":0.0052087354,"threshold_uncertainty_score":0.58302474},"labels":[],"label_agreement":null},{"id":"W2151059370","doi":"10.1287/inte.30.6.17.11631","title":"A Decision Support System for Planning Remanufacturing at Nortel Networks","year":2000,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Government of Ontario","keywords":"Remanufacturing; Plan (archaeology); Decision support system; Product (mathematics); Reverse logistics; Process (computing); Process management; Operations research; Computer science; Engineering; Business; Manufacturing engineering; Supply chain; Marketing","score_opus":0.013466556618708103,"score_gpt":0.23014641328825983,"score_spread":0.21667985666955172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151059370","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.051383786,0.0005827295,0.8463825,0.0015536615,0.00018336109,0.00069890905,0.0063271946,0.06851701,0.024370847],"genre_scores_gemma":[0.31542686,0.0007501237,0.65940803,0.00024617137,0.000075431526,0.0008581842,0.0071281386,0.0011637516,0.014943326],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909914,0.00024941424,0.00013327309,0.00015266189,0.00031200456,0.000053545533],"domain_scores_gemma":[0.997727,0.0012137211,0.00013799914,0.00020349259,0.0005815608,0.00013618515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021232762,0.000995662,0.00068553904,0.0017406257,0.000899974,0.0028526562,0.0011913225,0.0007178067,0.015453436],"category_scores_gemma":[0.005544346,0.0005197238,0.0005058506,0.0011235591,0.0003306605,0.0020133196,0.00092854624,0.00077195396,0.0032728065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083889137,0.00039169446,0.0074558486,0.0004938316,0.00015386811,0.0013697856,0.00094962114,0.28515962,0.012517745,0.040371165,0.05504662,0.5952513],"study_design_scores_gemma":[0.00014057623,0.000070441274,0.0007049561,0.00008061604,0.000045682093,0.00009313362,0.00010283266,0.93681127,0.005549827,0.008670149,0.047677267,0.00005324275],"about_ca_topic_score_codex":0.01524633,"about_ca_topic_score_gemma":0.013075972,"teacher_disagreement_score":0.015453436,"about_ca_system_score_codex":0.0014156159,"about_ca_system_score_gemma":0.002088985,"threshold_uncertainty_score":0.051696897},"labels":[],"label_agreement":null},{"id":"W2152294486","doi":"10.1287/inte.1110.0590","title":"Kimberly-Clark Latin America Builds an Optimization-Based System for Machine Scheduling","year":2011,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kimberly-Clark (Canada)","funders":"","keywords":"Scheduling (production processes); Sizing; Operations research; Production planning; Single-machine scheduling; Computer science; Job shop scheduling; Mathematical optimization; Production (economics); Engineering; Operations management; Schedule; Economics; Mathematics; Microeconomics","score_opus":0.021953395711161623,"score_gpt":0.22904342655600082,"score_spread":0.2070900308448392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152294486","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.041152976,0.00089588325,0.8672342,0.0019802165,0.00027587093,0.0008647403,0.001400928,0.015434876,0.070760325],"genre_scores_gemma":[0.332217,0.00094098714,0.6340644,0.0003741006,0.00007787514,0.00079493114,0.0020220757,0.0009276632,0.028581085],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951625,0.00013184908,0.00002480761,0.00013009159,0.0001201881,0.000076866774],"domain_scores_gemma":[0.9994931,0.00015793936,0.000052715455,0.00008453642,0.00014823437,0.00006350559],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010569551,0.0011854655,0.00068611326,0.0014039937,0.0013178883,0.0014013408,0.0016078423,0.0007798995,0.0119817015],"category_scores_gemma":[0.0017689916,0.0007107669,0.00074668473,0.002260116,0.0006931488,0.0009683966,0.001337764,0.001361131,0.0024698537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003488148,0.00022829171,0.0036980931,0.00023801388,0.00010792364,0.00024879578,0.00031098226,0.65483236,0.008106681,0.09035866,0.03706099,0.20446041],"study_design_scores_gemma":[0.000083950385,0.00006138721,0.00035622015,0.000024631283,0.000019557237,0.000029821142,0.000025744035,0.9367247,0.0032415956,0.005275124,0.054126967,0.00003017865],"about_ca_topic_score_codex":0.09794424,"about_ca_topic_score_gemma":0.08980526,"teacher_disagreement_score":0.09794424,"about_ca_system_score_codex":0.0037950885,"about_ca_system_score_gemma":0.006189279,"threshold_uncertainty_score":0.19474828},"labels":[],"label_agreement":null},{"id":"W2152306358","doi":"10.1287/inte.30.6.32.11625","title":"The Québec Ministry of Natural Resources Uses Linear Programming to Understand the Wood-Fiber Market","year":2000,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts (Québec); Université Laval","funders":"","keywords":"Christian ministry; Government (linguistics); Negotiation; Linear programming; Natural resource; Industrial organization; Fiber; Yield (engineering); Business; Computer science; Environmental economics; Economics; Political science","score_opus":0.010329851943537449,"score_gpt":0.23616173908635188,"score_spread":0.22583188714281444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152306358","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06634326,0.006939339,0.5451721,0.0315416,0.00032072075,0.0006301797,0.018141124,0.0017591588,0.32915246],"genre_scores_gemma":[0.6246296,0.006955412,0.2583367,0.0020009247,0.00012721945,0.00053737365,0.0048358627,0.00031604277,0.102260806],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993338,0.0002446403,0.000019837717,0.000091156864,0.00018771667,0.00012276784],"domain_scores_gemma":[0.9988372,0.0006815077,0.000095170355,0.00004437108,0.00029025364,0.000051519095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014634012,0.00087326486,0.00042133845,0.0013343799,0.0019254155,0.0033666636,0.00089398597,0.00088302523,0.008158478],"category_scores_gemma":[0.0021272728,0.0004944856,0.0005970013,0.0022209329,0.0011011311,0.0014182011,0.0004923283,0.0012927473,0.0007200924],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004451854,0.00008660882,0.0055753416,0.00016108232,0.000042809228,0.00016252059,0.00033204432,0.42262018,0.000647774,0.44185168,0.050058898,0.078416675],"study_design_scores_gemma":[0.000044345037,0.00004026007,0.004267975,0.00015307365,0.00002272396,0.00003586687,0.00048647303,0.7488171,0.00088666397,0.074769974,0.17040566,0.00006981473],"about_ca_topic_score_codex":0.939199,"about_ca_topic_score_gemma":0.95392865,"teacher_disagreement_score":0.97120875,"about_ca_system_score_codex":0.028791226,"about_ca_system_score_gemma":0.025786458,"threshold_uncertainty_score":0.20889592},"labels":[],"label_agreement":null},{"id":"W2155355405","doi":"10.1287/inte.1050.0175","title":"Developing the Reflective Practitioner—Designing an Undergraduate Class","year":2006,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Reflective Practices in Education","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University; University of Strathclyde","keywords":"Reflection (computer programming); Class (philosophy); Reflective practice; Process (computing); Action (physics); Action research; Statement (logic); Mathematics education; Psychology; Medical education; Engineering ethics; Engineering; Computer science; Pedagogy; Medicine; Political science; Artificial intelligence","score_opus":0.0507119137437996,"score_gpt":0.3914413770110575,"score_spread":0.34072946326725795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155355405","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32793862,0.0016009128,0.5476856,0.02869647,0.0036129171,0.017480083,0.00022827,0.002476306,0.07028089],"genre_scores_gemma":[0.2945991,0.00092022354,0.65691805,0.0052281017,0.0004156855,0.0049843956,0.00022741525,0.00034085507,0.0363662],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.989145,0.00617914,0.00053290377,0.0011886361,0.0019740737,0.0009804369],"domain_scores_gemma":[0.9821623,0.0060483697,0.0011270181,0.0024076563,0.0036915934,0.0045629763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020326225,0.0006574187,0.0004514083,0.0009090283,0.002597694,0.004862438,0.0028632297,0.0021439162,0.004448589],"category_scores_gemma":[0.032528892,0.000714026,0.00057014206,0.00035440308,0.002557379,0.0034593034,0.0036206394,0.003481968,0.0028511307],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025377204,0.0064486517,0.0077807955,0.0007685633,0.00003397936,0.0011943125,0.120973155,0.0018411231,0.027759498,0.03904187,0.05831367,0.7355906],"study_design_scores_gemma":[0.00038630428,0.005646889,0.008392831,0.0016694498,0.000061734194,0.0030630392,0.057556335,0.007032444,0.027312953,0.0400188,0.84862113,0.0002380048],"about_ca_topic_score_codex":0.00049295987,"about_ca_topic_score_gemma":0.0009579896,"teacher_disagreement_score":0.020326225,"about_ca_system_score_codex":0.001974026,"about_ca_system_score_gemma":0.0052028187,"threshold_uncertainty_score":0.10749662},"labels":[],"label_agreement":null},{"id":"W2162064622","doi":"10.1287/inte.2013.0702","title":"Editorial: The 10th Rothkopf Rankings of Universities’ Contributions to the INFORMS Practice Literature","year":2013,"lang":"en","type":"editorial","venue":"INFORMS Journal on Applied Analytics","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Visibility; Ranking (information retrieval); Yield (engineering); Norwegian; Library science; Sociology; Management; Geography; Computer science; Economics","score_opus":0.012210010728166132,"score_gpt":0.28122365836235536,"score_spread":0.2690136476341892,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162064622","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":"evaluation","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":"evaluation","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010700999,0.002480925,0.00014261775,0.04441765,0.95082504,0.000026195532,0.00009241357,0.0000680435,0.0018400889],"genre_scores_gemma":[0.0017865433,0.0034287453,0.00026848313,0.015082832,0.9653382,0.000037870584,0.00009486621,0.000089834575,0.0138727715],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9920769,0.0011003937,0.0007932077,0.00066704134,0.0047225947,0.00063998305],"domain_scores_gemma":[0.9641071,0.010186398,0.0018627892,0.000872289,0.019376839,0.0035945703],"candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.009001063,0.0031019137,0.0023091896,0.0070015043,0.004037855,0.007181729,0.0030776747,0.008243906,0.01477677],"category_scores_gemma":[0.040685937,0.00080477505,0.0020866184,0.0030294028,0.0029847485,0.0040546153,0.0013494138,0.0098307235,0.008650972],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018269448,0.000006793088,0.00003143933,0.00006865161,0.0000058003707,0.000048783524,0.00001251194,0.000020701425,0.00002875797,0.00015382004,0.996183,0.0034214733],"study_design_scores_gemma":[0.00005642634,0.00003789633,0.0006704646,0.00060440897,0.000037377216,0.00024788556,0.0001332368,0.00025715568,0.00023062962,0.0009135826,0.996783,0.000028084383],"about_ca_topic_score_codex":0.003564934,"about_ca_topic_score_gemma":0.008908361,"teacher_disagreement_score":0.9929985,"about_ca_system_score_codex":0.0051686335,"about_ca_system_score_gemma":0.005513432,"threshold_uncertainty_score":0.04943323},"labels":[],"label_agreement":null},{"id":"W2162564886","doi":"10.1287/inte.1030.0055","title":"The Canadian Pacific Railway Transforms Operations by Using Models to Develop Its Operating Plans","year":2004,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Pacific Railway (Canada)","funders":"","keywords":"Tonnage; Train; Productivity; Service (business); Operations research; Block (permutation group theory); Engineering; Suite; Fuel efficiency; Transport engineering; Rail freight transport; Heuristic; Operations management; Computer science; Business; Economics; Automotive engineering; Marketing","score_opus":0.039494680634362164,"score_gpt":0.2849870721228541,"score_spread":0.24549239148849195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162564886","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08418082,0.001187167,0.65149707,0.0039980737,0.0003831058,0.0007255739,0.0076018004,0.0033800763,0.24704632],"genre_scores_gemma":[0.58868694,0.0027944134,0.3717875,0.00034874916,0.00009343261,0.0004263317,0.005861748,0.000488482,0.029512519],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999302,0.00017375575,0.000025110072,0.00008521989,0.00032727903,0.000086565706],"domain_scores_gemma":[0.99898285,0.0003349201,0.000087192915,0.00009764892,0.00044217234,0.000055223278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010832755,0.0013040799,0.000445738,0.0020161124,0.0012216095,0.00243927,0.0012655751,0.0006543317,0.005940411],"category_scores_gemma":[0.00315789,0.0006038245,0.00093575084,0.0019521697,0.00076331483,0.0010520538,0.0010314466,0.0011089478,0.0008865779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017488628,0.000024623227,0.0017224376,0.00005506929,0.000029868983,0.000043379117,0.000082726365,0.9423507,0.00025659555,0.02317136,0.0061580325,0.026087752],"study_design_scores_gemma":[0.000012496321,0.000018955905,0.00094853865,0.000047162463,0.00002810881,0.000011030615,0.00015893867,0.96477437,0.00029894052,0.009734289,0.023940228,0.000027055476],"about_ca_topic_score_codex":0.8936855,"about_ca_topic_score_gemma":0.90253055,"teacher_disagreement_score":0.10631448,"about_ca_system_score_codex":0.012259905,"about_ca_system_score_gemma":0.020521538,"threshold_uncertainty_score":0.21388113},"labels":[],"label_agreement":null},{"id":"W2163689154","doi":"10.1287/inte.33.2.12.14465","title":"Applying Operations Research Techniques to Financial Markets","year":2003,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"University of Nottingham; London School of Economics and Political Science","keywords":"Financial market; Equity (law); Debt; Finance; Business; Financial modeling; Market data; Financial engineering; Economics","score_opus":0.13052742231364783,"score_gpt":0.42996205898317885,"score_spread":0.299434636669531,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163689154","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018054858,0.00380998,0.9877608,0.00088036293,0.00022358693,0.000096845964,0.00006223125,0.00018692526,0.0051736673],"genre_scores_gemma":[0.1512566,0.023911424,0.8154873,0.0007002161,0.0018748426,0.0010678106,0.0004083428,0.00017617161,0.005117314],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99320227,0.0033611564,0.00068173726,0.00053484377,0.0019419368,0.00027802069],"domain_scores_gemma":[0.99158734,0.006208008,0.0005788556,0.0005109706,0.00096700876,0.00014773027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0067342296,0.001954625,0.0018133026,0.0032601987,0.0007567659,0.0037948594,0.001275152,0.0014012388,0.0054877154],"category_scores_gemma":[0.016844733,0.0006169733,0.0015688259,0.005322897,0.0023128067,0.0031157192,0.0022259366,0.0036525128,0.0016366193],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001067572,0.00016182309,0.00097116583,0.0012662223,0.00023525974,0.00029703294,0.0004285857,0.178186,0.002157323,0.44764048,0.007826003,0.36072335],"study_design_scores_gemma":[0.00005746439,0.00010935891,0.0003758116,0.00024646457,0.00005435604,0.00015169695,0.00014852188,0.40144455,0.0013150424,0.5692023,0.026850529,0.00004381218],"about_ca_topic_score_codex":0.0019627241,"about_ca_topic_score_gemma":0.0010393223,"teacher_disagreement_score":0.0067342296,"about_ca_system_score_codex":0.0012977985,"about_ca_system_score_gemma":0.002876664,"threshold_uncertainty_score":0.03561449},"labels":[],"label_agreement":null},{"id":"W2167612934","doi":"10.1287/inte.1030.0049","title":"Preferred Scenarios in the Sport of Curling","year":2004,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Federated Co-operatives (Canada)","funders":"","keywords":"Championship; Curling; Shot (pellet); World championship; Point (geometry); Class (philosophy); Advertising; Team sport; Tipping point (physics); Marketing; Psychology; Computer science; Engineering; Mathematics; Artificial intelligence; Athletes; Business","score_opus":0.03536256942786613,"score_gpt":0.23215535338871035,"score_spread":0.1967927839608442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167612934","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8841854,0.00065031945,0.022665199,0.0030654855,0.00007988077,0.00012279442,0.0007234594,0.00007046744,0.088436976],"genre_scores_gemma":[0.9950283,0.00013721373,0.0030754153,0.000170235,0.000011111985,0.000033928463,0.00023156332,0.000012124224,0.0013000219],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9949175,0.0032470122,0.00018809027,0.00037364324,0.0008441697,0.00042958668],"domain_scores_gemma":[0.99367565,0.00329959,0.00070442626,0.00041524658,0.00086161966,0.0010434124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0050938046,0.00057268277,0.0003639034,0.0014915016,0.0016212194,0.004615413,0.00074668723,0.0021379702,0.0073870597],"category_scores_gemma":[0.019857317,0.00030450994,0.0004434989,0.0007687393,0.0018276768,0.0031075235,0.0018468122,0.0013187225,0.00090385793],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034352343,0.0010097085,0.32766065,0.0011099457,0.00086451595,0.0050398693,0.046810266,0.04380177,0.0062482217,0.43021145,0.026839985,0.10696841],"study_design_scores_gemma":[0.0004335805,0.001115212,0.1273179,0.00070390623,0.00021718603,0.004997499,0.09788133,0.0973637,0.0021518886,0.5465045,0.12080896,0.0005043277],"about_ca_topic_score_codex":0.007892395,"about_ca_topic_score_gemma":0.019661248,"teacher_disagreement_score":0.007892395,"about_ca_system_score_codex":0.0014176934,"about_ca_system_score_gemma":0.00085981813,"threshold_uncertainty_score":0.026938915},"labels":[],"label_agreement":null},{"id":"W2169931118","doi":"10.1287/inte.1070.0332","title":"Chrysler and J. D. Power: Pioneering Scientific Price Customization in the Automobile Industry","year":2008,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Chrysler (Canada)","funders":"","keywords":"Lease; Economics; Product (mathematics); Market power; Incentive; Pricing strategies; Multinomial logistic regression; Industrial organization; Business; Microeconomics; Finance; Monopoly; Computer science","score_opus":0.020588390831361564,"score_gpt":0.23045557100791123,"score_spread":0.20986718017654965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169931118","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03715286,0.020708308,0.6153277,0.2376206,0.0037840137,0.00051348406,0.0007960091,0.0011209551,0.08297602],"genre_scores_gemma":[0.31398574,0.04269539,0.5150931,0.026020281,0.004124577,0.0007434757,0.00037669178,0.00071578845,0.09624494],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9962494,0.0012915379,0.00016077749,0.0008823408,0.001230379,0.00018554469],"domain_scores_gemma":[0.98097056,0.014393701,0.00046987418,0.00079685845,0.0027142568,0.00065471977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0077097993,0.0010864198,0.00067112717,0.0029524376,0.0013904567,0.0028809016,0.0012720599,0.0022898961,0.00490481],"category_scores_gemma":[0.021883242,0.00094448816,0.0013417585,0.0016554664,0.0032291953,0.005252701,0.00256569,0.005733377,0.0014705284],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015892937,0.00053967827,0.007271177,0.0003924543,0.00011657944,0.0004158632,0.0013515408,0.02579478,0.0017366444,0.48381874,0.14657377,0.3318299],"study_design_scores_gemma":[0.000115321105,0.000387924,0.0032313534,0.00044354523,0.00009802168,0.0005231997,0.0006554242,0.07704912,0.007176092,0.3374049,0.57266355,0.00025161484],"about_ca_topic_score_codex":0.017206293,"about_ca_topic_score_gemma":0.012046355,"teacher_disagreement_score":0.017206293,"about_ca_system_score_codex":0.0047430065,"about_ca_system_score_gemma":0.004916696,"threshold_uncertainty_score":0.04077381},"labels":[],"label_agreement":null},{"id":"W2203748571","doi":"10.1287/inte.2015.0815","title":"ASP, The Art and Science of Practice: Academia-Industry Interfacing in Operations Research in Montréal","year":2015,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Business Strategy and Innovation","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Interfacing; Engineering ethics; Field (mathematics); Management; Technology transfer; Spin offs; Engineering; Engineering management; Sociology; Political science; Business; Knowledge management; Computer science; Mathematics; Economics; Industrial organization; Law","score_opus":0.09572344529637218,"score_gpt":0.3560162520420642,"score_spread":0.26029280674569205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2203748571","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39601466,0.033083905,0.011130544,0.19465435,0.0010316742,0.0004928173,0.0005062655,0.00031924894,0.36276653],"genre_scores_gemma":[0.9496216,0.004777005,0.0028682363,0.0027784551,0.00011202963,0.00007307552,0.00009538601,0.000066787776,0.039607316],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9775243,0.010717629,0.00055942015,0.0015296576,0.0052702753,0.0043986784],"domain_scores_gemma":[0.971094,0.010381747,0.0022649672,0.0014787028,0.004138792,0.010641931],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0143205235,0.00045478562,0.0003779417,0.0022979467,0.017955108,0.01692328,0.002688319,0.0023904524,0.012504441],"category_scores_gemma":[0.020866562,0.0006616854,0.00032234646,0.008880898,0.028267521,0.006381829,0.011767785,0.0035039263,0.0006511271],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002034184,0.00021729199,0.032769937,0.0005882787,0.00007074417,0.0052698352,0.2818348,0.002422966,0.003095088,0.37110013,0.06671775,0.23570979],"study_design_scores_gemma":[0.000046673304,0.00019192838,0.061624236,0.00038858046,0.000022942697,0.00050405774,0.2275002,0.00092883775,0.0008222778,0.015420075,0.69239414,0.00015603816],"about_ca_topic_score_codex":0.8616143,"about_ca_topic_score_gemma":0.8985157,"teacher_disagreement_score":0.9820449,"about_ca_system_score_codex":0.11663582,"about_ca_system_score_gemma":0.15122542,"threshold_uncertainty_score":0.8462561},"labels":[],"label_agreement":null},{"id":"W2537516281","doi":"10.1287/inte.2016.0863","title":"Power System Operator in Mexico Reveals Millions in Savings by Updating Its Short-Term Thermal Unit Commitment Model","year":2016,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Electric Power System Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Alberta","keywords":"Power system simulation; Integer programming; Operations research; Operator (biology); Lagrangian relaxation; Computer science; Thermal power station; Operational planning; Process (computing); Mathematical optimization; Term (time); Economic dispatch; Electric power system; Engineering; Power (physics); Economics; Mathematics; Operating system; Waste management","score_opus":0.012622626418105801,"score_gpt":0.22828881889855795,"score_spread":0.21566619248045216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2537516281","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5525564,0.0022894228,0.22519085,0.022243092,0.00092659664,0.0002429711,0.016466146,0.0037237506,0.17636071],"genre_scores_gemma":[0.9338439,0.0007223122,0.0388271,0.00047225217,0.0000582185,0.00010487769,0.0050969487,0.00021637337,0.020658094],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999678,0.000092553535,0.000011120197,0.000062491454,0.00010594055,0.000049892282],"domain_scores_gemma":[0.9994307,0.00021390736,0.000054025943,0.000054695844,0.00021378825,0.000032892658],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007018088,0.00042973782,0.0003284211,0.00028326883,0.00061973266,0.0011168038,0.0007906932,0.0005941041,0.004762628],"category_scores_gemma":[0.0017548918,0.00030049658,0.0003510055,0.0007442396,0.00026122716,0.0009901098,0.00040740918,0.0012998718,0.0003652913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028768138,0.00009295768,0.011638209,0.00012657407,0.00011440349,0.00018747941,0.00014443527,0.80768746,0.001221866,0.03300192,0.05394299,0.09155407],"study_design_scores_gemma":[0.00007731101,0.00011652492,0.00943572,0.00005447576,0.000068119385,0.000070929076,0.00023281468,0.92901164,0.0016395313,0.0061086784,0.05313972,0.00004453396],"about_ca_topic_score_codex":0.16183786,"about_ca_topic_score_gemma":0.2097379,"teacher_disagreement_score":0.16183786,"about_ca_system_score_codex":0.0032479514,"about_ca_system_score_gemma":0.0023611719,"threshold_uncertainty_score":0.32179177},"labels":[],"label_agreement":null},{"id":"W2594829375","doi":"10.1287/inte.2016.0864","title":"A Review of Scheduling Problems and Research Opportunities in Motion Picture Exhibition","year":2017,"lang":"en","type":"review","venue":"INFORMS Journal on Applied Analytics","topic":"Cinema and Media Studies","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Exhibition; Movie theater; Film industry; Scheduling (production processes); Computer science; Context (archaeology); Scale (ratio); Engineering; Data science; Multimedia; Visual arts; Art; Operations management; History; Geography","score_opus":0.4224786817422227,"score_gpt":0.3940462467131995,"score_spread":0.028432435029023206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594829375","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00037668878,0.9949922,0.0017142035,0.00054786884,0.00022334456,0.0000062872177,0.0000378473,0.000010551201,0.0020910078],"genre_scores_gemma":[0.0034818936,0.9939622,0.0012690771,0.00017357204,0.0005237934,0.000009824237,0.000075525044,0.0000058943874,0.00049813546],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994618,0.00013018254,0.00007688128,0.000120704186,0.00016167479,0.00004876211],"domain_scores_gemma":[0.9970902,0.0022339649,0.00019086657,0.000050697556,0.0003650812,0.000069164555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00128386,0.0012005211,0.0014197775,0.0024625105,0.00049550616,0.0016142052,0.0011727532,0.0016725439,0.004664534],"category_scores_gemma":[0.0037580659,0.00063963543,0.0010321229,0.007197314,0.0005897074,0.0025119963,0.00058399636,0.0014289859,0.0012718212],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008280088,0.00018652616,0.00095649826,0.028594872,0.00017919886,0.00018881416,0.00014631673,0.011775675,0.0006138115,0.034041982,0.051001564,0.872232],"study_design_scores_gemma":[0.000031831747,0.00023966268,0.0033561185,0.014777184,0.00030751762,0.00088922266,0.00041449507,0.0060390695,0.0005771732,0.03802431,0.93524647,0.0000969134],"about_ca_topic_score_codex":0.0036055949,"about_ca_topic_score_gemma":0.0034342404,"teacher_disagreement_score":0.004664534,"about_ca_system_score_codex":0.0011085174,"about_ca_system_score_gemma":0.0023693102,"threshold_uncertainty_score":0.015604436},"labels":[],"label_agreement":null},{"id":"W2762403164","doi":"10.1287/inte.2017.0906","title":"Calibrated Route Finder: Improving the Safety, Environmental Consciousness, and Cost Effectiveness of Truck Routing in Sweden","year":2017,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Truck; Standardization; Fuel efficiency; Process (computing); Operations research; Routing (electronic design automation); Transport engineering; Analytics; Externality; Key (lock); Environmental economics; Telematics; Computer science; Business; Engineering; Computer security; Economics; Automotive engineering; Telecommunications; Microeconomics","score_opus":0.012539391289504149,"score_gpt":0.22985461102650862,"score_spread":0.21731521973700446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762403164","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92702585,0.00051746826,0.06037108,0.0004148951,0.00007350797,0.00009052593,0.0011605145,0.004577409,0.005768739],"genre_scores_gemma":[0.9278448,0.0003009969,0.06793052,0.000033369324,0.000013346959,0.00004132848,0.0019472111,0.00025795348,0.0016303356],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910235,0.00039785926,0.000051702697,0.000171077,0.0001937477,0.00008329187],"domain_scores_gemma":[0.998315,0.00080403686,0.00017879136,0.00021223901,0.00038824213,0.00010183213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014531153,0.0007765782,0.0006068219,0.001966626,0.0005748582,0.0013808787,0.00080366916,0.00081092847,0.0018880484],"category_scores_gemma":[0.006215602,0.0004034492,0.0004801805,0.001380619,0.00040579442,0.0017767096,0.0009929839,0.0004873575,0.00052719616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009426898,0.0006034989,0.045450993,0.0003989244,0.00019683733,0.00054736517,0.0012729764,0.6220727,0.004267525,0.004824132,0.010666768,0.30875567],"study_design_scores_gemma":[0.00010210292,0.00033740344,0.01731233,0.000060210106,0.000089067464,0.00019278334,0.0013628419,0.9639882,0.00516457,0.0045355577,0.0067739733,0.00008091067],"about_ca_topic_score_codex":0.033639677,"about_ca_topic_score_gemma":0.032981254,"teacher_disagreement_score":0.033639677,"about_ca_system_score_codex":0.001555921,"about_ca_system_score_gemma":0.002455031,"threshold_uncertainty_score":0.06688774},"labels":[],"label_agreement":null},{"id":"W2764060445","doi":"10.1287/inte.2017.0918","title":"Introduction: 2016 Daniel H. Wagner Prize for Excellence in Operations Research Practice","year":2017,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Staffing; Competition (biology); Analytics; CLARITY; Excellence; Productivity; Originality; Automotive industry; Quality (philosophy); Presentation (obstetrics); Resource (disambiguation); Engineering management; Operations research; Computer science; Management; Operations management; Engineering; Creativity; Data science; Political science; Economics","score_opus":0.05058330178861114,"score_gpt":0.33731420827402964,"score_spread":0.2867309064854185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2764060445","genre_codex":"other","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020189523,0.048379373,0.011143124,0.19552301,0.2660182,0.00037770666,0.004387479,0.0012904755,0.47086158],"genre_scores_gemma":[0.018147768,0.04051159,0.0049543018,0.013140381,0.057873115,0.00024645394,0.0028854124,0.0012536488,0.8609874],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9948894,0.00038339934,0.00034322956,0.0006586332,0.0031693785,0.0005560224],"domain_scores_gemma":[0.9907928,0.0009532886,0.00037124156,0.00032936622,0.0046826773,0.002870599],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0062638093,0.0015392789,0.001086289,0.0025167514,0.0015161515,0.010916297,0.0015261633,0.0036401313,0.1994627],"category_scores_gemma":[0.014223636,0.00043585716,0.0008143558,0.001993463,0.0011479127,0.0050796466,0.0033704292,0.003805781,0.11503192],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002328044,0.000014860711,0.000057128404,0.00011018259,0.0000026999023,0.00001804191,0.000032964803,0.00009064557,0.00012195205,0.007028489,0.94104797,0.051451802],"study_design_scores_gemma":[0.000007239701,0.00002186436,0.00026921966,0.0002468671,0.00000216381,0.00004563874,0.000049559898,0.0001294943,0.00012411858,0.0037488043,0.99534386,0.000011094256],"about_ca_topic_score_codex":0.002038455,"about_ca_topic_score_gemma":0.0036555263,"teacher_disagreement_score":0.1994627,"about_ca_system_score_codex":0.0055766613,"about_ca_system_score_gemma":0.005250101,"threshold_uncertainty_score":0.66726923},"labels":[],"label_agreement":null},{"id":"W2785506546","doi":"10.1287/inte.2017.0930","title":"Discrete-Event Simulation Modeling Unlocks Value for the Jansen Potash Project","year":2018,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Amec Foster Wheeler (Canada); BHP (Canada)","funders":"","keywords":"Net present value; Discrete event simulation; Production (economics); Engineering; Operations research; Dice; Potash; Operations management; Event (particle physics); Economics; Simulation; Mathematics","score_opus":0.03419948282742167,"score_gpt":0.2935306931228241,"score_spread":0.2593312102954024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2785506546","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3780222,0.0006974983,0.4908163,0.008636693,0.00050794776,0.000644178,0.004072723,0.0021381413,0.114464425],"genre_scores_gemma":[0.92714655,0.00039102056,0.058370598,0.00028282555,0.00005149045,0.0003133464,0.0015379578,0.00026045673,0.011645707],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990396,0.0003888494,0.000036900605,0.00012360231,0.00028664546,0.00012432439],"domain_scores_gemma":[0.9942392,0.0042136484,0.00023388663,0.00029370416,0.00071982335,0.00029976296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029875804,0.0006308318,0.000664574,0.00058416417,0.0009157673,0.0032649082,0.0017117515,0.0015796722,0.0065288],"category_scores_gemma":[0.008843659,0.000708552,0.0010268213,0.00061001943,0.000851943,0.0020222198,0.0017673377,0.0024065168,0.00046382798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007785756,0.000048418344,0.0019805236,0.00003544673,0.000016474973,0.00007894228,0.00008014721,0.9710605,0.00020543158,0.020107742,0.0014193541,0.004889191],"study_design_scores_gemma":[0.000014608736,0.00001493546,0.00018442102,0.000013040974,0.000005694637,0.0000053433755,0.00003354283,0.9929765,0.000099451914,0.0043365527,0.0023091407,0.000006727395],"about_ca_topic_score_codex":0.068847254,"about_ca_topic_score_gemma":0.046431515,"teacher_disagreement_score":0.068847254,"about_ca_system_score_codex":0.003077537,"about_ca_system_score_gemma":0.0045275376,"threshold_uncertainty_score":0.13689303},"labels":[],"label_agreement":null},{"id":"W2885299987","doi":"10.1287/inte.2018.0947","title":"Solving the Whistler-Blackcomb Mega Day Challenge","year":2018,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Winter Sports Injuries and Performance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Whistler; Mega-; Advertising; Aeronautics; Engineering; Business; Physics","score_opus":0.023405799602491572,"score_gpt":0.281363314647048,"score_spread":0.25795751504455644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885299987","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6523978,0.0008513274,0.30462268,0.0028053871,0.00027139022,0.0006160802,0.0023514042,0.0010130117,0.03507087],"genre_scores_gemma":[0.73503643,0.00033890954,0.2505482,0.00030005685,0.000069944675,0.00047450335,0.0023077847,0.00020371286,0.01072053],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912614,0.00030610332,0.000045870704,0.00020974567,0.0000874592,0.00022476561],"domain_scores_gemma":[0.9966834,0.0025670258,0.00016784428,0.00011370914,0.00024373479,0.00022425372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013380317,0.001089167,0.0009708076,0.0003974451,0.00059835386,0.0012727809,0.0011484956,0.0021262607,0.007563419],"category_scores_gemma":[0.0060904543,0.0004945132,0.0009263663,0.0006224509,0.0005237827,0.0011859478,0.0012686629,0.0013285935,0.0007023518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021566478,0.00036196638,0.004204333,0.00025568926,0.000053940214,0.0001987358,0.00017446888,0.9464818,0.0007014506,0.0060552675,0.0060588606,0.0352377],"study_design_scores_gemma":[0.000075515585,0.00018400134,0.0012284135,0.00002496303,0.000018366656,0.00003207169,0.00035401512,0.98998487,0.0004912323,0.005801832,0.0017903806,0.000014332423],"about_ca_topic_score_codex":0.02688165,"about_ca_topic_score_gemma":0.02957947,"teacher_disagreement_score":0.02688165,"about_ca_system_score_codex":0.0008819729,"about_ca_system_score_gemma":0.0034741755,"threshold_uncertainty_score":0.053450346},"labels":[],"label_agreement":null},{"id":"W2902906171","doi":"10.1287/inte.2018.0959","title":"Metro Uses a Simulation-Optimization Approach to Improve Fare-Collection Shift Scheduling","year":2018,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Integer programming; Scheduling (production processes); Discrete event simulation; Computer science; Operations research; Mathematical optimization; Simulation; Engineering; Mathematics; Algorithm","score_opus":0.026314478494525704,"score_gpt":0.30246534036897915,"score_spread":0.2761508618744534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2902906171","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029883303,0.00011906929,0.96073526,0.00025330205,0.00012091056,0.00014468271,0.00013537015,0.0014762043,0.007131935],"genre_scores_gemma":[0.61001694,0.00023296298,0.38441575,0.00012964601,0.00005735553,0.00029938042,0.0003183539,0.00036863948,0.0041609015],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993437,0.00027083745,0.0000335726,0.000106212494,0.00016414704,0.00008148582],"domain_scores_gemma":[0.99843794,0.00091031776,0.00010053611,0.00017312272,0.00029436362,0.000083733765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012786612,0.0014724061,0.0015153945,0.0009929305,0.00080106617,0.0009780397,0.0012379958,0.0010246744,0.0028142757],"category_scores_gemma":[0.0026981144,0.0010536079,0.0013872649,0.0010265767,0.00051984715,0.0008807812,0.0008706229,0.0014714258,0.0004861889],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028744887,0.000046914156,0.00018051632,0.0000108673885,0.000028396102,0.000008616881,0.0000096478,0.9925054,0.0003873932,0.0014004498,0.0001902364,0.005202848],"study_design_scores_gemma":[0.000008735141,0.000016770055,0.000025712847,0.0000011715857,0.0000046601813,0.0000023803398,0.000002667024,0.9988827,0.00027939086,0.0003693672,0.00040318226,0.0000032249147],"about_ca_topic_score_codex":0.023301357,"about_ca_topic_score_gemma":0.020461734,"teacher_disagreement_score":0.023301357,"about_ca_system_score_codex":0.0016223235,"about_ca_system_score_gemma":0.0019758502,"threshold_uncertainty_score":0.046331465},"labels":[],"label_agreement":null},{"id":"W2916399584","doi":"10.1287/inte.2018.0969","title":"Automated Pathologist Scheduling at The Ottawa Hospital","year":2019,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Electricity Association; Ottawa Hospital; University of Ottawa","funders":"Department of Pathology and Laboratory Medicine, University of North Carolina School of Medicine","keywords":"Scheduling (production processes); Medical laboratory; Medicine; Computer science; Medical physics; Medical emergency; Pathology; Operations management; Engineering","score_opus":0.030700366507547122,"score_gpt":0.3653847770548557,"score_spread":0.3346844105473086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916399584","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7974834,0.0026015185,0.10399345,0.012556408,0.0013137566,0.0018609314,0.014891432,0.02381028,0.041488845],"genre_scores_gemma":[0.86618847,0.00067684456,0.1086232,0.0006696912,0.0001709889,0.00016848058,0.0055880565,0.0005495046,0.017364796],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975593,0.0005369931,0.00019124652,0.0006042818,0.00067379145,0.00043440107],"domain_scores_gemma":[0.992718,0.001959604,0.00059558015,0.0006218366,0.002319125,0.0017857855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021698033,0.00070636114,0.0003897216,0.0017684897,0.002314232,0.0019562617,0.0011566333,0.00063534925,0.007463896],"category_scores_gemma":[0.0063661705,0.0007215363,0.00047732846,0.0017765446,0.00057923124,0.00069214875,0.0009801507,0.00076048035,0.0016882078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0046720067,0.00078411575,0.09153824,0.00047669708,0.00027478184,0.0017405099,0.0025327082,0.19276069,0.029564254,0.005038626,0.17648122,0.49413618],"study_design_scores_gemma":[0.00078042905,0.0006833726,0.103470266,0.00013826482,0.00017955157,0.00051588373,0.0037156434,0.70040226,0.030773574,0.0048998133,0.15405469,0.00038614735],"about_ca_topic_score_codex":0.5083251,"about_ca_topic_score_gemma":0.57564205,"teacher_disagreement_score":0.5083251,"about_ca_system_score_codex":0.01308478,"about_ca_system_score_gemma":0.026308922,"threshold_uncertainty_score":0.9891409},"labels":[],"label_agreement":null},{"id":"W2917137472","doi":"10.1287/inte.2018.0972","title":"Operations Research Enables Auction to Repurpose Television Spectrum for Next-Generation Wireless Technologies","year":2019,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Spectrum auction; Wireless; Telecommunications; Business; Computer science; Advertising; Marketing; Auction theory","score_opus":0.23834671815167754,"score_gpt":0.4288633834914778,"score_spread":0.19051666533980025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2917137472","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013733328,0.001970527,0.88769054,0.0035086595,0.00058257533,0.00036949097,0.0004597205,0.0024319007,0.08925333],"genre_scores_gemma":[0.5259953,0.004311528,0.44447288,0.0006576681,0.00068307004,0.0005492214,0.0011810195,0.000585761,0.02156351],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99591994,0.0020928935,0.00021708041,0.0003092558,0.001163256,0.00029762942],"domain_scores_gemma":[0.988117,0.008623117,0.0006332562,0.0012356472,0.0010733278,0.0003176872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010873971,0.00091647124,0.0005923067,0.001784857,0.0007220546,0.0047945846,0.0010619992,0.0010928988,0.014128178],"category_scores_gemma":[0.01664508,0.0005505817,0.0011049281,0.0023743121,0.0011775705,0.004127393,0.0015957617,0.0019481194,0.0028004542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048468448,0.00045211223,0.0025084263,0.00032975298,0.00016934631,0.00021664279,0.00022929594,0.09435497,0.0033479736,0.6302108,0.029206922,0.23848905],"study_design_scores_gemma":[0.00025661348,0.00041661318,0.00079267775,0.00014342707,0.00009746388,0.00012587613,0.00019241938,0.5635326,0.004545617,0.3402144,0.0895891,0.000093197435],"about_ca_topic_score_codex":0.0045156362,"about_ca_topic_score_gemma":0.003199574,"teacher_disagreement_score":0.014128178,"about_ca_system_score_codex":0.0017144318,"about_ca_system_score_gemma":0.0029365108,"threshold_uncertainty_score":0.057507753},"labels":[],"label_agreement":null},{"id":"W3000986316","doi":"10.1287/inte.2019.1022","title":"Analytics and Optimization Reduce Sewage Overflows to Protect Community Waterways in Kentucky","year":2020,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Tetra Tech (Canada)","funders":"","keywords":"Combined sewer; Analytics; Metropolitan area; Sanitary sewer; Routing (electronic design automation); Maximization; Environmental science; General partnership; Computer science; Environmental engineering; Computer network; Stormwater; Business; Data science; Finance; Geography","score_opus":0.03268766417471507,"score_gpt":0.2363283965739841,"score_spread":0.20364073239926905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3000986316","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.983422,0.00015989829,0.007339174,0.0010424372,0.000025361474,0.00012970476,0.001037691,0.00077811355,0.0060656415],"genre_scores_gemma":[0.9860533,0.00012961484,0.00662924,0.000069030546,0.000009227821,0.000053171763,0.0010649369,0.00006707645,0.005924412],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99946505,0.00011109608,0.000023020928,0.00013844631,0.0001209739,0.0001415116],"domain_scores_gemma":[0.99898213,0.0002547625,0.000117676514,0.00008528707,0.0003777918,0.00018238336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063723646,0.0006003753,0.0004155316,0.0007558351,0.0012368702,0.001249979,0.00051606516,0.0005078469,0.0040919874],"category_scores_gemma":[0.002112014,0.00031826828,0.00032277204,0.000821297,0.00057711423,0.0009403461,0.0011845919,0.0007289848,0.0003828521],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011331349,0.0009865562,0.13531786,0.00020083533,0.00016498931,0.00047514538,0.0005943442,0.63085943,0.013928645,0.003205912,0.018628348,0.19450475],"study_design_scores_gemma":[0.00015030365,0.0006294651,0.09106879,0.00005249784,0.000072636016,0.000033639717,0.0023000012,0.8826869,0.010032813,0.0045165103,0.00840807,0.000048462727],"about_ca_topic_score_codex":0.43251282,"about_ca_topic_score_gemma":0.5912878,"teacher_disagreement_score":0.43251282,"about_ca_system_score_codex":0.0050773676,"about_ca_system_score_gemma":0.0074704695,"threshold_uncertainty_score":0.8599906},"labels":[],"label_agreement":null},{"id":"W3012135359","doi":"10.1287/inte.2020.1031","title":"A Decision Support System for Attended Home Services","year":2020,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Decision support system; Business; Electricity; Distribution (mathematics); Operations research; Operations management; Marketing; Computer science; Engineering","score_opus":0.014227646118997355,"score_gpt":0.22602564371901762,"score_spread":0.21179799760002027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3012135359","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033227403,0.00048104546,0.9009275,0.0009457218,0.0003372408,0.00085709017,0.0030277143,0.051309925,0.008886403],"genre_scores_gemma":[0.4479051,0.0003706324,0.5363899,0.0005653372,0.00016586886,0.0010065959,0.0041301064,0.00063224527,0.008834368],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989812,0.00022530746,0.00014743186,0.00025655233,0.0002963111,0.00009320322],"domain_scores_gemma":[0.9981554,0.0009735259,0.00013084504,0.00016541166,0.00038853489,0.00018623681],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012270082,0.00094967167,0.0009137661,0.0010269725,0.0008345374,0.0022015122,0.0016300225,0.0013248968,0.014725548],"category_scores_gemma":[0.0040048137,0.0003927443,0.0007772311,0.000758288,0.00030021995,0.0012936329,0.0012616052,0.0012874054,0.003793578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026603914,0.0012503201,0.005947372,0.00073582487,0.0004051209,0.0026632391,0.00062893133,0.287983,0.020237513,0.021377623,0.06105432,0.5950564],"study_design_scores_gemma":[0.00034654158,0.0001971945,0.0007226687,0.00006698854,0.00006869803,0.00020439754,0.00009430578,0.94957936,0.006918723,0.010626282,0.031122789,0.000051977593],"about_ca_topic_score_codex":0.003906855,"about_ca_topic_score_gemma":0.002624371,"teacher_disagreement_score":0.014725548,"about_ca_system_score_codex":0.0007354842,"about_ca_system_score_gemma":0.0011097578,"threshold_uncertainty_score":0.04926181},"labels":[],"label_agreement":null},{"id":"W3044751814","doi":"10.1287/inte.2020.1027","title":"Barrick’s Turquoise Ridge Gold Mine Optimizes Underground Production Scheduling Operations","year":2020,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Barrick Gold (Canada)","funders":"","keywords":"Production (economics); Time horizon; Schedule; Resource (disambiguation); Horizon; Computer science; Operations research; Mining engineering; Engineering; Business; Mathematics; Finance; Economics","score_opus":0.026205937141039422,"score_gpt":0.2249408667407473,"score_spread":0.19873492959970787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3044751814","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7318402,0.00034872355,0.23107575,0.0011747963,0.00009588275,0.00020228577,0.0005092302,0.00079135114,0.03396168],"genre_scores_gemma":[0.9111705,0.00009327176,0.08044544,0.00007946505,0.000010690636,0.000067383306,0.00026282392,0.00009370971,0.00777691],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979657,0.000056193458,0.0000063547013,0.000048723305,0.00003536015,0.000056770135],"domain_scores_gemma":[0.9996774,0.00016836406,0.00003490366,0.000023026212,0.000058336132,0.000037843725],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004794633,0.0005261503,0.00048742714,0.0004151913,0.00040594456,0.00068342424,0.0005634092,0.00076976966,0.0031055447],"category_scores_gemma":[0.0012808962,0.00029289408,0.00031214854,0.00034630677,0.0003934572,0.00050572574,0.00048355997,0.00051372824,0.00022304176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007161544,0.00007271866,0.0015043903,0.000023859056,0.000014221169,0.000058543705,0.00003164542,0.9726335,0.0011056062,0.0032870562,0.0015642848,0.019632546],"study_design_scores_gemma":[0.000016571432,0.00004505343,0.00041445383,0.000004475842,0.0000040153614,0.000010657406,0.0000461079,0.9960078,0.00044114317,0.0019282387,0.001078113,0.0000033572967],"about_ca_topic_score_codex":0.023400735,"about_ca_topic_score_gemma":0.041272923,"teacher_disagreement_score":0.023400735,"about_ca_system_score_codex":0.00096617924,"about_ca_system_score_gemma":0.0016365702,"threshold_uncertainty_score":0.046529055},"labels":[],"label_agreement":null},{"id":"W3129384632","doi":"10.1287/inte.2022.1132","title":"Optimization Helps Scheduling Nursing Staff at the Long-Term Care Homes of the City of Toronto","year":2022,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Scheduling (production processes); Status quo; Computer science; Absenteeism; Schedule; Long-term care; Operations management; Operations research; Nursing; Nurse scheduling problem; Business; Job shop scheduling; Medicine; Flow shop scheduling; Economics; Engineering; Management","score_opus":0.053871199729866065,"score_gpt":0.3475262837933807,"score_spread":0.2936550840635146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3129384632","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6890147,0.0011496035,0.2574488,0.0019419617,0.00015623703,0.00067089323,0.003342281,0.0024907875,0.04378479],"genre_scores_gemma":[0.85804087,0.00044612252,0.13351442,0.00008093252,0.00001799131,0.00015989666,0.001492296,0.00014668074,0.006100733],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996314,0.00012361821,0.000020414336,0.00006419654,0.00008789384,0.00007246379],"domain_scores_gemma":[0.99897325,0.0005978208,0.000092218244,0.000030074181,0.0002099339,0.00009676618],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006522537,0.00061789254,0.00024487634,0.00050918513,0.0007546591,0.0008987538,0.00041726368,0.00025655693,0.004700556],"category_scores_gemma":[0.0023258408,0.00023386988,0.00030248216,0.0007138348,0.00022384194,0.00031390213,0.00030560026,0.00033503887,0.00029673352],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003025041,0.00016362821,0.012436823,0.00031374785,0.000055619686,0.00014884514,0.00045542922,0.82606405,0.0043999995,0.0042588646,0.014677607,0.13672279],"study_design_scores_gemma":[0.00004462731,0.000099130295,0.0070612016,0.000025382278,0.000032138578,0.000018156548,0.00035986083,0.9806506,0.00239098,0.002126965,0.007168778,0.000022132313],"about_ca_topic_score_codex":0.34436327,"about_ca_topic_score_gemma":0.44795105,"teacher_disagreement_score":0.6556367,"about_ca_system_score_codex":0.0044301255,"about_ca_system_score_gemma":0.007034791,"threshold_uncertainty_score":0.6847177},"labels":[],"label_agreement":null},{"id":"W3152824712","doi":"10.1287/inte.2020.1070","title":"The Impact of Age Demographics on Interpreting and Applying Population-Wide Infection Fatality Rates for COVID-19","year":2021,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Pandemic; Government (linguistics); Population; Workforce; Jurisdiction; Health care; Outbreak; Case fatality rate; Coronavirus disease 2019 (COVID-19); Demographics; Business; Public health; Geography; Demography; Political science; Economic growth; Medicine; Disease; Environmental health; Economics; Sociology; Nursing; Virology","score_opus":0.17293612935711253,"score_gpt":0.4690570621306652,"score_spread":0.29612093277355267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152824712","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72076464,0.011544155,0.17049807,0.013415203,0.0018188361,0.0016636786,0.022985566,0.00047175627,0.056838147],"genre_scores_gemma":[0.9700627,0.0014088203,0.023051493,0.0009803892,0.00024657714,0.0003045498,0.0025438129,0.000086355125,0.0013154255],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.97180563,0.017939474,0.002132959,0.0026117878,0.0044185743,0.0010914778],"domain_scores_gemma":[0.87068605,0.08680879,0.01594632,0.007965434,0.017135125,0.0014583798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0535661,0.00081164896,0.0005356677,0.004047985,0.0012355503,0.0029711355,0.0021014642,0.00081459293,0.0020591246],"category_scores_gemma":[0.27977,0.0004387826,0.0014615108,0.0035989163,0.0012328135,0.00212223,0.0019776828,0.0015548443,0.0006165795],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001630618,0.000040162504,0.9260642,0.00033549717,0.00073536875,0.00024154726,0.0041169096,0.008929283,0.00022760357,0.00769037,0.0063564316,0.04509964],"study_design_scores_gemma":[0.000030255796,0.00028958454,0.8872819,0.0011303395,0.0008166756,0.0007649973,0.012507459,0.039612852,0.0025067586,0.013395753,0.041513566,0.00014984414],"about_ca_topic_score_codex":0.3280959,"about_ca_topic_score_gemma":0.332391,"teacher_disagreement_score":0.3280959,"about_ca_system_score_codex":0.0034739955,"about_ca_system_score_gemma":0.0062227636,"threshold_uncertainty_score":0.65237236},"labels":[],"label_agreement":null},{"id":"W3158898498","doi":"10.1287/inte.2020.1055","title":"A Machine Learning-Based System for Predicting Service-Level Failures in Supply Chains","year":2021,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Supply chain; Computer science; Service level; Service management; Service (business); Stock (firearms); Risk analysis (engineering); Supply chain management; Operations management; Operations research; Reliability engineering; Business; Engineering; Marketing","score_opus":0.02284518305943014,"score_gpt":0.23545439099428783,"score_spread":0.21260920793485769,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158898498","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19439109,0.0003949386,0.6787864,0.0008607213,0.00017018738,0.00085262995,0.0039348206,0.115068905,0.0055403565],"genre_scores_gemma":[0.7530941,0.00013648596,0.24008425,0.00021648053,0.00004056601,0.000430415,0.00276029,0.00031638055,0.0029209913],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945706,0.00010947937,0.00006145097,0.00019995058,0.00012877797,0.000043218224],"domain_scores_gemma":[0.99778533,0.0012092105,0.00023191192,0.00024271547,0.00040102034,0.0001298278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012133913,0.0010789448,0.0005972198,0.0013685655,0.0006315341,0.00088148145,0.0013067015,0.0010264843,0.005084734],"category_scores_gemma":[0.0051416205,0.00042159518,0.0003889055,0.0009943448,0.0002857982,0.0015110249,0.00071963965,0.0010003066,0.0016048369],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012340831,0.0014131478,0.025825424,0.00030981368,0.00018562442,0.0005351166,0.0004169257,0.47316137,0.013560704,0.0023266894,0.016297827,0.46473333],"study_design_scores_gemma":[0.00001972485,0.000063479914,0.0011742532,0.000009125991,0.000009178149,0.000022220689,0.000015213314,0.9943772,0.0022557252,0.0010185154,0.0010211112,0.000014233058],"about_ca_topic_score_codex":0.010484954,"about_ca_topic_score_gemma":0.0074730436,"teacher_disagreement_score":0.010484954,"about_ca_system_score_codex":0.0012116872,"about_ca_system_score_gemma":0.0012516291,"threshold_uncertainty_score":0.020847857},"labels":[],"label_agreement":null},{"id":"W3162849139","doi":"10.1287/inte.2021.1080","title":"Theory-Driven Practical Approach to Integrate R&amp;D and Production Planning for Portfolio Management in Agribusiness","year":2021,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Production (economics); Flexibility (engineering); Modern portfolio theory; Portfolio; Computer science; Function (biology); Operations research; Population; Agribusiness; Yield (engineering); Economics; Microeconomics; Mathematics; Agriculture; Geography; Statistics; Financial economics","score_opus":0.20873042411796147,"score_gpt":0.4650840388606759,"score_spread":0.25635361474271445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3162849139","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017054683,0.00008079227,0.9863898,0.001450674,0.00003470163,0.00014511895,0.000031268857,0.00016195427,0.0100001525],"genre_scores_gemma":[0.14063835,0.00034187845,0.85232687,0.0005408511,0.000094172996,0.0006424104,0.00009372447,0.000108437525,0.0052133054],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9936427,0.0033101335,0.00034292994,0.0008159668,0.0015649591,0.0003232816],"domain_scores_gemma":[0.9914483,0.005151867,0.0005717656,0.0015593438,0.0009906178,0.00027809455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010159329,0.0014753634,0.0008095256,0.0017693251,0.0012854855,0.0054519423,0.0033129642,0.0030120239,0.008332413],"category_scores_gemma":[0.015157867,0.0013500269,0.001432982,0.0013861648,0.0044470644,0.0047205016,0.0036646747,0.004101146,0.0015875704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018039142,0.00012736823,0.000683077,0.00011464643,0.0000467571,0.00013243227,0.0001600204,0.2471748,0.00097392284,0.70970047,0.0019801345,0.038888346],"study_design_scores_gemma":[0.00002735968,0.000067733105,0.00012460163,0.000058298723,0.000014402477,0.000053660304,0.00010697875,0.5569253,0.0011377598,0.42913514,0.012324149,0.000024577928],"about_ca_topic_score_codex":0.004630764,"about_ca_topic_score_gemma":0.006070101,"teacher_disagreement_score":0.010159329,"about_ca_system_score_codex":0.0051163333,"about_ca_system_score_gemma":0.0071887528,"threshold_uncertainty_score":0.053728282},"labels":[],"label_agreement":null},{"id":"W3174371370","doi":"10.1287/inte.2021.1073","title":"Seasonal Inventory Management Model for Raw Materials in Steel Industry","year":2021,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Raw material; Yard; Economic shortage; Business; Operations management; Environmental science; Supply chain; Operations research; Port (circuit theory); Inventory theory; Inventory control; Waste management; Engineering","score_opus":0.027895588298759915,"score_gpt":0.25822013543219885,"score_spread":0.23032454713343894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174371370","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16411036,0.0010204633,0.8068737,0.0015375385,0.00022108556,0.0002655325,0.002084104,0.0005955561,0.023291761],"genre_scores_gemma":[0.94510126,0.0007407303,0.031820223,0.00016816062,0.00008611597,0.00031481773,0.0009040128,0.000077539895,0.020787263],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918014,0.00017803714,0.000053952732,0.00021274653,0.00016209477,0.00021295802],"domain_scores_gemma":[0.99925905,0.00026951724,0.00016612206,0.000032140168,0.00018339875,0.000089681365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011926226,0.0012193373,0.0013654266,0.0008085045,0.00080496294,0.001803714,0.0030466006,0.0019171331,0.0054030856],"category_scores_gemma":[0.0015860694,0.0009143344,0.0016945105,0.0012140631,0.00083823095,0.0016110996,0.0010421427,0.0013540483,0.00064376567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000290419,0.00002282703,0.00057700864,0.000032052623,0.000017180208,0.00013801809,0.00004238846,0.9883211,0.00050854293,0.008003651,0.0004411155,0.0018670865],"study_design_scores_gemma":[0.000006554398,0.000013107678,0.00011118906,0.0000024593953,0.0000071021973,0.000010728315,0.0000099290355,0.9982116,0.000047505673,0.0013351209,0.0002401954,0.000004555761],"about_ca_topic_score_codex":0.034087636,"about_ca_topic_score_gemma":0.018582737,"teacher_disagreement_score":0.034087636,"about_ca_system_score_codex":0.0022434625,"about_ca_system_score_gemma":0.0021917892,"threshold_uncertainty_score":0.06777841},"labels":[],"label_agreement":null},{"id":"W3211496389","doi":"10.1287/inte.2021.1089","title":"Inventory Management Using a Weekly Review (<i>s</i>, <i>S</i>) Policy at the Bank of Canada","year":2021,"lang":"en","type":"review","venue":"INFORMS Journal on Applied Analytics","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Inventory management; Activity-based costing; Business; Unintended consequences; Actuarial science; Operations management; Finance; Economics; Accounting; Political science","score_opus":0.04584932154932919,"score_gpt":0.2831113914955137,"score_spread":0.23726206994618448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3211496389","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00079822546,0.9155241,0.0011318378,0.0280788,0.007440758,0.00046150893,0.0015917344,0.00023413933,0.044738807],"genre_scores_gemma":[0.009544391,0.9371131,0.0029625404,0.009396747,0.0017061684,0.0002762354,0.0012022296,0.00007412481,0.0377244],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99608237,0.00047726074,0.0005187898,0.00020929346,0.0024853433,0.00022689985],"domain_scores_gemma":[0.97185916,0.0027885428,0.0021269736,0.0006780448,0.020669017,0.0018782581],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059900973,0.0005991137,0.0010669027,0.006557409,0.0013320664,0.0031300916,0.0013102138,0.0013497493,0.010110124],"category_scores_gemma":[0.016097631,0.0003381799,0.00054743805,0.008390893,0.0010542851,0.0015005505,0.0008490406,0.0018052015,0.0035406526],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029853249,0.00002899058,0.00039459782,0.012703479,0.000055779325,0.000069263224,0.00012917165,0.00011862504,0.00064101245,0.0037614082,0.56180376,0.420264],"study_design_scores_gemma":[0.000006264373,0.0000137994075,0.0014486399,0.0060169306,0.000037965878,0.000044288,0.000037782822,0.000029275989,0.0001558786,0.00018958462,0.9920087,0.000010935872],"about_ca_topic_score_codex":0.30192557,"about_ca_topic_score_gemma":0.5527169,"teacher_disagreement_score":0.30192557,"about_ca_system_score_codex":0.011528367,"about_ca_system_score_gemma":0.06582781,"threshold_uncertainty_score":0.6003363},"labels":[],"label_agreement":null},{"id":"W4211052544","doi":"10.1287/inte.1100.0522","title":"Contributors","year":2010,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business; Computer science","score_opus":0.006747082050140396,"score_gpt":0.2145491325432109,"score_spread":0.2078020504930705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4211052544","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015242541,0.0058217873,0.0029682224,0.028015519,0.04190818,0.00029127125,0.004861,0.0017633865,0.91284645],"genre_scores_gemma":[0.004709171,0.00326652,0.0011571181,0.0050339317,0.0040912973,0.00013130499,0.0035723473,0.00051862246,0.97751963],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99830174,0.00020769556,0.000082970655,0.00033918838,0.0008156627,0.00025269593],"domain_scores_gemma":[0.9949936,0.00038612477,0.00013307157,0.0004563937,0.00270443,0.0013262683],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0012614856,0.0008126635,0.0006889652,0.0018496896,0.0022000754,0.0064468835,0.0019150795,0.0022189114,0.623277],"category_scores_gemma":[0.008026362,0.00029325258,0.0005229351,0.0020553598,0.0005394061,0.004392178,0.0037162318,0.00185984,0.46673605],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024024444,0.00001820426,0.00020708777,0.000081112434,0.0000024732103,0.000056581393,0.00010525941,0.000039720373,0.000121556965,0.0059634964,0.9300174,0.06336317],"study_design_scores_gemma":[0.0000022643478,0.0000046749765,0.00013342946,0.000053260104,0.000001083123,0.00004310688,0.00009346245,0.000016699176,0.000032603013,0.0007676934,0.99884915,0.0000025276386],"about_ca_topic_score_codex":0.002136031,"about_ca_topic_score_gemma":0.002959201,"teacher_disagreement_score":0.376723,"about_ca_system_score_codex":0.0019478118,"about_ca_system_score_gemma":0.0033648387,"threshold_uncertainty_score":0.5373496},"labels":[],"label_agreement":null},{"id":"W4213066012","doi":"10.1287/inte.1100.0553","title":"Contributors","year":2011,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business; Computer science; Engineering","score_opus":0.13311805828135007,"score_gpt":0.34242367671483553,"score_spread":0.20930561843348547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213066012","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015073098,0.0051740184,0.0032602185,0.020695386,0.0365425,0.0003367101,0.00695005,0.0015672928,0.9239665],"genre_scores_gemma":[0.004882718,0.0029832886,0.0014751086,0.003779558,0.002854231,0.00015538835,0.005062182,0.00064063113,0.97816694],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980301,0.00024647027,0.000108285545,0.00038331858,0.000934255,0.00029747887],"domain_scores_gemma":[0.99517006,0.000376872,0.00011319721,0.00044681306,0.0027277642,0.0011653253],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0014993373,0.0009274345,0.000710056,0.0021771756,0.0024365438,0.0066082804,0.0019735347,0.0024369229,0.6460754],"category_scores_gemma":[0.007786978,0.0003193491,0.00056995,0.0025001813,0.0006076414,0.0042042774,0.0038875442,0.0019687777,0.47389463],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028429558,0.000020501038,0.00019714405,0.00010162149,0.0000028071465,0.000058076275,0.00010101411,0.000053931868,0.00013252854,0.006604299,0.9228281,0.0698716],"study_design_scores_gemma":[0.000002534311,0.000004977111,0.00017000127,0.000055932782,9.908447e-7,0.00004376044,0.00009314937,0.000017887438,0.000040429666,0.00080766535,0.9987601,0.0000026335128],"about_ca_topic_score_codex":0.0028489952,"about_ca_topic_score_gemma":0.0037613607,"teacher_disagreement_score":0.35392457,"about_ca_system_score_codex":0.0024715764,"about_ca_system_score_gemma":0.0038457774,"threshold_uncertainty_score":0.5048304},"labels":[],"label_agreement":null},{"id":"W4245764878","doi":"10.1287/inte.30.4.94.11649","title":"Book Reviews","year":2000,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Modeling, Simulation, and Optimization","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Commission; Space (punctuation); Library science; Ask price; Operations research; Data science; Political science; Engineering; Economics; Law","score_opus":0.046638770165563115,"score_gpt":0.3121370211433926,"score_spread":0.2654982509778295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245764878","genre_codex":"review","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00089184096,0.4986383,0.002870665,0.022462541,0.06567036,0.000380318,0.003906514,0.0011548767,0.40402463],"genre_scores_gemma":[0.0038235118,0.3100885,0.0040515685,0.015034798,0.020090958,0.00029413743,0.0061433963,0.0006888089,0.63978434],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.996801,0.00030699762,0.00020594026,0.00037727604,0.0021559233,0.00015290729],"domain_scores_gemma":[0.9948019,0.00085721206,0.00034974702,0.00027638307,0.0030925819,0.0006222268],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0010221209,0.0011554688,0.0016394007,0.0042455867,0.001041829,0.0058910046,0.0018129532,0.0018132342,0.2578384],"category_scores_gemma":[0.009121615,0.0005295486,0.00079040736,0.006337264,0.00060437777,0.0029230856,0.0015030404,0.0025598188,0.26136905],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000130186845,0.000022733719,0.000045417837,0.0007267564,0.0000074809295,0.000052941574,0.00003035923,0.000061026458,0.00014874477,0.001293996,0.9025012,0.095096394],"study_design_scores_gemma":[0.0000037659324,0.000010648382,0.000095878226,0.0005491494,0.000004701292,0.00015649489,0.000022391292,0.000015281932,0.000035336303,0.0005230537,0.9985784,0.000004891685],"about_ca_topic_score_codex":0.0015903072,"about_ca_topic_score_gemma":0.002707246,"teacher_disagreement_score":0.74216163,"about_ca_system_score_codex":0.0012789152,"about_ca_system_score_gemma":0.002999786,"threshold_uncertainty_score":0.8625554},"labels":[],"label_agreement":null},{"id":"W4247553243","doi":"10.1287/inte.1110.0609","title":"Contributors","year":2011,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business; Computer science","score_opus":0.0281790540709295,"score_gpt":0.24338214228324614,"score_spread":0.21520308821231665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247553243","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017306071,0.006998526,0.002770638,0.0379441,0.07000699,0.0004327021,0.0053665265,0.0016414172,0.8731085],"genre_scores_gemma":[0.0040478446,0.0033940314,0.0012179076,0.0061590546,0.0051794574,0.00015142922,0.0034526272,0.0004975554,0.9759001],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99810827,0.00023423252,0.0001016467,0.0003458548,0.0009120901,0.00029793993],"domain_scores_gemma":[0.99284995,0.0005795095,0.00016195767,0.00051595015,0.004146757,0.0017459847],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0016005704,0.00090182124,0.0006728137,0.0024172075,0.0029339248,0.007100529,0.0019070684,0.002407575,0.58924687],"category_scores_gemma":[0.010068467,0.0003222887,0.0005120238,0.0023218973,0.0005785851,0.0043962854,0.0035783895,0.0021400524,0.40015095],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016143313,0.000012948712,0.00014403478,0.00006684187,0.0000014920862,0.000039385144,0.0000965616,0.000025261119,0.00007818693,0.0037505557,0.9528731,0.04289548],"study_design_scores_gemma":[0.0000019151207,0.000003839416,0.00013131004,0.00005577372,8.8954016e-7,0.00003776438,0.00011632935,0.000011744836,0.000027877964,0.0005654607,0.9990447,0.0000022588592],"about_ca_topic_score_codex":0.0029542937,"about_ca_topic_score_gemma":0.0041177906,"teacher_disagreement_score":0.41075313,"about_ca_system_score_codex":0.002570709,"about_ca_system_score_gemma":0.0040029804,"threshold_uncertainty_score":0.58588946},"labels":[],"label_agreement":null},{"id":"W4252228566","doi":"10.1287/inte.1110.0581","title":"Contributors","year":2011,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Business","score_opus":0.1919850467501503,"score_gpt":0.3883384410576747,"score_spread":0.19635339430752438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252228566","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019095514,0.0062648635,0.0044651134,0.047861986,0.06729647,0.0005785352,0.010466648,0.0022414627,0.8589153],"genre_scores_gemma":[0.005258845,0.0032797845,0.0017157788,0.007358167,0.0046410207,0.00019117855,0.0054780366,0.0005888217,0.9714884],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982811,0.00024912023,0.00010144291,0.00032191176,0.0008223308,0.00022416211],"domain_scores_gemma":[0.99249434,0.00065820914,0.00017998247,0.0005693246,0.0046980167,0.0014000896],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0016888573,0.00093783543,0.00070928945,0.0024799753,0.0025742133,0.006118189,0.0018537862,0.002261862,0.5905955],"category_scores_gemma":[0.011132234,0.00033640905,0.00053215143,0.0022397425,0.00052433537,0.0038998316,0.0032784205,0.002003604,0.40047625],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017251545,0.000011758205,0.00018284912,0.000052068728,0.0000016162852,0.000039603416,0.000077775825,0.00004094072,0.000059582027,0.003663931,0.954828,0.041024756],"study_design_scores_gemma":[0.0000026146145,0.0000044414714,0.00015191571,0.00005363518,0.0000011150358,0.000043516568,0.000115104776,0.00002560096,0.00003217606,0.00079718966,0.9987697,0.000002900262],"about_ca_topic_score_codex":0.0037458243,"about_ca_topic_score_gemma":0.00453056,"teacher_disagreement_score":0.40940452,"about_ca_system_score_codex":0.0026084983,"about_ca_system_score_gemma":0.003971681,"threshold_uncertainty_score":0.58396584},"labels":[],"label_agreement":null},{"id":"W4256526873","doi":"10.1287/inte.31.3s.108.9685","title":"Implementing and Evaluating SilverScreener: A Marketing Management Support System for Movie Exhibitors","year":2001,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Movie theater; Attendance; Revenue; Path (computing); Path analysis (statistics); Computer science; Marketing; Advertising; Operations research; Business; Multimedia; Engineering; Economics; Art; Visual arts","score_opus":0.09065147209015902,"score_gpt":0.3933037154119106,"score_spread":0.3026522433217516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4256526873","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95648336,0.0000348838,0.032777097,0.00023186761,0.000028284672,0.00069385476,0.0003621108,0.0071356297,0.0022529024],"genre_scores_gemma":[0.87912196,0.000063202395,0.115664124,0.00009002957,0.000013330319,0.00031206803,0.0013421297,0.0001819749,0.0032112272],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9990282,0.00046177054,0.00008533079,0.000162751,0.00020320163,0.000058676866],"domain_scores_gemma":[0.9950925,0.002966713,0.0003420984,0.00063039607,0.00057328166,0.00039496252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031901014,0.0007243776,0.00037112267,0.000539174,0.00035609576,0.00086175173,0.0013631644,0.0007101186,0.003062635],"category_scores_gemma":[0.009058533,0.00035322402,0.00026494949,0.00030642416,0.0002654623,0.0015322019,0.0008167388,0.00051263155,0.00078995514],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011289852,0.013027637,0.066236146,0.0009079396,0.00037691323,0.0012030734,0.0035299847,0.14390852,0.07532457,0.0039645485,0.02198304,0.65824777],"study_design_scores_gemma":[0.0012564191,0.0064634345,0.032221437,0.00005108467,0.00022474295,0.00017144551,0.0007052778,0.9073964,0.040440556,0.001210411,0.009723124,0.00013573571],"about_ca_topic_score_codex":0.0049897786,"about_ca_topic_score_gemma":0.005604703,"teacher_disagreement_score":0.0049897786,"about_ca_system_score_codex":0.0010603099,"about_ca_system_score_gemma":0.0006652669,"threshold_uncertainty_score":0.016871035},"labels":[],"label_agreement":null},{"id":"W4367676883","doi":"10.1287/inte.2023.1164","title":"Bombardier Aftermarket Demand Forecast with Machine Learning","year":2023,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Group for Research in Decision Analysis; HEC Montréal; Mila - Quebec Artificial Intelligence Institute; Bombardier (Canada)","funders":"","keywords":"Spare part; Demand forecasting; Computer science; Analytics; On demand; Process (computing); Economic shortage; Operations research; Data mining; Engineering; Operations management","score_opus":0.07595793931106345,"score_gpt":0.3423356359571896,"score_spread":0.2663776966461261,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367676883","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30235216,0.0007725545,0.6844288,0.00080753653,0.00015661963,0.00010220974,0.0011830634,0.0050210496,0.005175973],"genre_scores_gemma":[0.8771587,0.00025044868,0.118808985,0.00010344259,0.00010028935,0.00006953376,0.0013970478,0.00008141105,0.0020300918],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996253,0.000093385956,0.000025776244,0.00009788725,0.00010910462,0.00004843146],"domain_scores_gemma":[0.9988907,0.0006022713,0.0001103981,0.00010135443,0.00025919135,0.000036052323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080030237,0.00071091217,0.00068489584,0.0010193858,0.00030403127,0.0006548926,0.0005983853,0.0005176678,0.0010903863],"category_scores_gemma":[0.0026922007,0.00027570542,0.0005609248,0.0010139593,0.00014947008,0.0009397693,0.00049622485,0.0012203669,0.00049494515],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000063401414,0.00007589177,0.0036328372,0.000020631614,0.000048343732,0.000026201042,0.000025463189,0.88681054,0.0010004009,0.00055169617,0.0017291072,0.10601548],"study_design_scores_gemma":[8.0142274e-7,0.0000032831924,0.00022166496,8.0747964e-7,0.0000011991697,8.6744086e-7,0.0000015689525,0.99935883,0.0001353443,0.00019979426,0.00007446055,0.0000013670128],"about_ca_topic_score_codex":0.035889134,"about_ca_topic_score_gemma":0.021514624,"teacher_disagreement_score":0.96411085,"about_ca_system_score_codex":0.00085580564,"about_ca_system_score_gemma":0.0007172409,"threshold_uncertainty_score":0.07136053},"labels":[],"label_agreement":null},{"id":"W4401952593","doi":"10.1287/inte.2023.0027","title":"Estimating Road Construction Costs with Explainable Machine Learning","year":2024,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministère des Transports; Polytechnique Montréal","funders":"","keywords":"Computer science; Transport engineering; Artificial intelligence; Machine learning; Engineering","score_opus":0.004908218599376482,"score_gpt":0.20715264379367995,"score_spread":0.20224442519430347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401952593","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.120207004,0.00019046092,0.87754655,0.0002944329,0.000013275693,0.000038916307,0.00032362118,0.00024205327,0.0011436738],"genre_scores_gemma":[0.8608541,0.00015686505,0.13740706,0.000032177548,0.00003047424,0.00007007134,0.0006350763,0.000025989699,0.0007882579],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99872214,0.00060046714,0.00006362312,0.0001896742,0.00032622274,0.00009793657],"domain_scores_gemma":[0.9909223,0.0062450054,0.0013273674,0.00086808886,0.0005331492,0.00010408392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001950228,0.0008152385,0.0007165843,0.0018221368,0.00029170694,0.0010953784,0.0012633723,0.0010535226,0.0016094109],"category_scores_gemma":[0.012900504,0.0004984608,0.0008336397,0.0014772754,0.0005974652,0.0021214313,0.0010522522,0.0013414532,0.00014133088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002543481,0.00004831842,0.0044231256,0.00003087175,0.00005728151,0.000038742757,0.00003403122,0.94469285,0.000193745,0.023652948,0.00035491865,0.02644772],"study_design_scores_gemma":[0.0000038042474,0.000018213412,0.0013990082,0.0000061785145,0.000009018322,0.0000113055685,0.000011301084,0.96539545,0.00025021302,0.032673817,0.0002136366,0.0000079277415],"about_ca_topic_score_codex":0.0054221894,"about_ca_topic_score_gemma":0.006012133,"teacher_disagreement_score":0.0054221894,"about_ca_system_score_codex":0.0012668703,"about_ca_system_score_gemma":0.00083182106,"threshold_uncertainty_score":0.010781229},"labels":[],"label_agreement":null},{"id":"W4404536325","doi":"10.1287/inte.2023.0069","title":"Freight Gateway Consolidation for Purolator International Using Integer Programming","year":2024,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; DuPont (Canada); Saint Mary's University","funders":"","keywords":"Consolidation (business); Integer programming; Gateway (web page); Computer science; Business; Operations research; Computer network; Engineering; World Wide Web; Finance; Algorithm","score_opus":0.028474612331637006,"score_gpt":0.300931678086638,"score_spread":0.272457065755001,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404536325","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13714215,0.0013475477,0.73233724,0.0020453397,0.00023105416,0.0007798878,0.0013412563,0.000970251,0.12380527],"genre_scores_gemma":[0.71462697,0.0019182246,0.24656568,0.00025040764,0.00009700451,0.00044125348,0.0014426039,0.00033416468,0.034323644],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951065,0.00014218445,0.000013537563,0.00008257376,0.000111787944,0.00013926477],"domain_scores_gemma":[0.9996691,0.00014204177,0.000036527694,0.000020371308,0.00009138994,0.00004056584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010719019,0.0010299643,0.00066866796,0.000975613,0.0010291763,0.0037799033,0.0009821932,0.0007691852,0.007931501],"category_scores_gemma":[0.0017548567,0.0006064738,0.00091460714,0.0014113548,0.00042845242,0.0019013381,0.00095859496,0.0014232872,0.00064551114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002623938,0.000053440755,0.0008961638,0.00003466516,0.000010921065,0.00005341691,0.0000373215,0.9519245,0.00031025874,0.019435436,0.003266008,0.02395152],"study_design_scores_gemma":[0.0000051473403,0.000017310009,0.0001413091,0.00002065885,0.0000076003435,0.0000065911627,0.000071392256,0.99269897,0.00019469268,0.0036187684,0.0032120144,0.0000054431393],"about_ca_topic_score_codex":0.15208362,"about_ca_topic_score_gemma":0.20590422,"teacher_disagreement_score":0.15208362,"about_ca_system_score_codex":0.0064750994,"about_ca_system_score_gemma":0.007497633,"threshold_uncertainty_score":0.30239683},"labels":[],"label_agreement":null},{"id":"W4408906315","doi":"10.1287/inte.2023.0073","title":"OCP Optimizes Its Supply Chain for Africa","year":2025,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Supply chain; Business; Chain (unit); Marketing; Physics","score_opus":0.01710053685614881,"score_gpt":0.23301539891681167,"score_spread":0.21591486206066285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408906315","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14513044,0.0013153576,0.7612515,0.0024594467,0.00032452826,0.00077416864,0.0034982632,0.003267451,0.08197882],"genre_scores_gemma":[0.4948473,0.0008589013,0.47939333,0.00025482767,0.00009702285,0.00039436822,0.0027238734,0.0006800954,0.020750292],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99930596,0.00022946023,0.00002899298,0.00013800194,0.00016563202,0.00013208737],"domain_scores_gemma":[0.9990707,0.00038244287,0.00009694966,0.00013039645,0.00024100262,0.00007846717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001453914,0.0014015851,0.00090934755,0.0013452402,0.0008756225,0.0023450225,0.00084556924,0.0010176983,0.013264143],"category_scores_gemma":[0.0031291142,0.0007134199,0.0009089083,0.0025717265,0.00052567426,0.0014281016,0.0013753015,0.0010873993,0.0014676675],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016551849,0.000078820034,0.0015181183,0.00021018714,0.00005896967,0.000102038255,0.00008688,0.84987146,0.0010854554,0.01729204,0.008581522,0.12094902],"study_design_scores_gemma":[0.000031839005,0.00008466735,0.00038139478,0.000029213075,0.000017557682,0.00002543557,0.00007428512,0.9773168,0.0007392931,0.012514043,0.00877649,0.0000090242265],"about_ca_topic_score_codex":0.019180644,"about_ca_topic_score_gemma":0.022034088,"teacher_disagreement_score":0.019180644,"about_ca_system_score_codex":0.0024767313,"about_ca_system_score_gemma":0.0038552594,"threshold_uncertainty_score":0.044372976},"labels":[],"label_agreement":null},{"id":"W4409800764","doi":"10.1287/inte.2024.0157","title":"Co-Creating an Analytical Mindset at a Financial Technology Platform","year":2025,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"FinTech, Crowdfunding, Digital Finance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Mindset; Key (lock); Equity (law); Business; Venture capital; Finance; Process management; Knowledge management; Computer science; Political science; Computer security","score_opus":0.018469864682620414,"score_gpt":0.27203044353704703,"score_spread":0.2535605788544266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409800764","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.523207,0.001856539,0.1914948,0.063280776,0.0014225276,0.00063335156,0.000106397805,0.00047969783,0.21751894],"genre_scores_gemma":[0.9452418,0.00059998385,0.039022364,0.001869199,0.00027093288,0.00024589544,0.000055547964,0.00015132644,0.01254306],"study_design_codex":"qualitative","study_design_gemma":"not_applicable","domain_scores_codex":[0.9614859,0.029622458,0.0005913785,0.0022005702,0.004114124,0.0019855709],"domain_scores_gemma":[0.9397037,0.040574055,0.0037648287,0.0044483887,0.0037654496,0.007743554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04127782,0.00089659204,0.0006166788,0.006306399,0.014523522,0.039086726,0.0022761812,0.00522178,0.0053516054],"category_scores_gemma":[0.047830444,0.000505994,0.0008179192,0.002876735,0.021195156,0.027039906,0.032377314,0.0045485985,0.0015788835],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014205097,0.0002850729,0.010247342,0.00041999575,0.000086295266,0.002535747,0.51513296,0.0014696219,0.0052372534,0.38443688,0.008203672,0.07180307],"study_design_scores_gemma":[0.00004088537,0.00020540536,0.0024121578,0.0006572952,0.00004546718,0.0015036013,0.43299118,0.0038170828,0.0025275738,0.35699007,0.19871028,0.000098988516],"about_ca_topic_score_codex":0.0007681066,"about_ca_topic_score_gemma":0.0012629974,"teacher_disagreement_score":0.04127782,"about_ca_system_score_codex":0.0044152606,"about_ca_system_score_gemma":0.012153294,"threshold_uncertainty_score":0.21830052},"labels":[],"label_agreement":null},{"id":"W4412573616","doi":"10.1287/inte.2024.0152","title":"Long-Term Open-Pit Mine Planning with Large Neighborhood Search","year":2025,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Rio Tinto (Canada)","funders":"","keywords":"Term (time); Open-pit mining; Mining engineering; Computer science; Environmental science; Geology; Physics","score_opus":0.0202792902292711,"score_gpt":0.2782746126544821,"score_spread":0.257995322425211,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412573616","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01794748,0.0002639777,0.977015,0.0002910184,0.00005140656,0.00008551715,0.00013866091,0.00045808384,0.00374872],"genre_scores_gemma":[0.440225,0.00021473857,0.55369747,0.00015426183,0.00006108739,0.00033045426,0.0004105387,0.00020988002,0.0046965205],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994862,0.000185796,0.000021562815,0.00011831647,0.00012210483,0.000065910324],"domain_scores_gemma":[0.99858946,0.00093022006,0.00011959107,0.00010244505,0.0001483456,0.00010986116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001053215,0.000805578,0.0014682359,0.0006312879,0.0008551197,0.0009846316,0.0022526016,0.0016133117,0.0042877602],"category_scores_gemma":[0.0036350316,0.0006887197,0.0010599889,0.00081554474,0.0007827299,0.0016768664,0.002180795,0.0015165082,0.0005154654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041336905,0.00004611777,0.0005021254,0.00004277021,0.000030406265,0.000079920144,0.00004009193,0.9751893,0.00033874784,0.0072251908,0.0013704845,0.015093543],"study_design_scores_gemma":[0.0000074304803,0.000013549892,0.000035466863,0.000003381844,0.0000041935,0.000009767126,0.000010361695,0.996172,0.0000870263,0.0032314388,0.0004223813,0.0000030542042],"about_ca_topic_score_codex":0.013626429,"about_ca_topic_score_gemma":0.024207728,"teacher_disagreement_score":0.013626429,"about_ca_system_score_codex":0.00089956686,"about_ca_system_score_gemma":0.0021741728,"threshold_uncertainty_score":0.027094245},"labels":[],"label_agreement":null},{"id":"W4414537747","doi":"10.1287/inte.2025.0247","title":"Redesigning Zoning Systems for Equitable and Efficient Last-Mile Delivery at Ninja Van","year":2025,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Software deployment; Zoning; Workload; Vehicle routing problem; Routing (electronic design automation); Key (lock); Voronoi diagram","score_opus":0.011573711498491434,"score_gpt":0.22742319398194966,"score_spread":0.21584948248345823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414537747","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08618417,0.00028328752,0.9044853,0.0003290436,0.0000967176,0.00019811127,0.00015917199,0.0015587979,0.00670547],"genre_scores_gemma":[0.74716437,0.00015229943,0.25009143,0.000052631618,0.000016867923,0.00009261138,0.00018958526,0.00015948064,0.0020807616],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993843,0.00016814462,0.000023919249,0.00010613662,0.00012455483,0.00019295422],"domain_scores_gemma":[0.99953437,0.000106798674,0.000075763746,0.000058318437,0.00014539018,0.000079368685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011042835,0.00057997036,0.00051213976,0.0006379508,0.00091079605,0.0012807406,0.0011887024,0.0005050381,0.003046214],"category_scores_gemma":[0.0019008677,0.00035797103,0.00038837644,0.0005622847,0.0005795537,0.0010357113,0.0017640801,0.00078806945,0.00039237321],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055995628,0.000037206057,0.0014253784,0.000040097962,0.000018919814,0.00003632935,0.00010453462,0.94134897,0.0041987454,0.011843552,0.001441312,0.039449085],"study_design_scores_gemma":[0.00001125868,0.000037950856,0.00036119716,0.000006928721,0.000007064718,0.000015354019,0.00008086075,0.9924791,0.0011652984,0.002767531,0.0030564019,0.000011082778],"about_ca_topic_score_codex":0.04194084,"about_ca_topic_score_gemma":0.048484053,"teacher_disagreement_score":0.04194084,"about_ca_system_score_codex":0.0018750171,"about_ca_system_score_gemma":0.0029307518,"threshold_uncertainty_score":0.083393455},"labels":[],"label_agreement":null}]}